Breath biomarkers of active pulmonary tuberculosis

Nanoscale Sensor Technologies for Disease Detection via Volatolomics

The detection of many diseases is missed because of delayed diagnoses or the low efficacy of some treatments. This emphasizes the urgent need for inexpensive and minimally invasive technologies that would allow efficient early detection, stratifying the population for personalized therapy, and improving the efficacy of rapid bed-side assessment of treatment. An emerging approach that has a high potential to fulfill these needs is based on so-called "volatolomics", namely, chemical processes involving profiles of highly volatile organic compounds (VOCs) emitted from body fluids, including breath, skin, urine and blood. This article presents a didactic review of some of the main advances related to the use of nanomaterial-based solid-state and flexible sensors, and related artificially intelligent sensing arrays for the detection and monitoring of disease with volatolomics. The article attempts to review the technological gaps and confounding factors related to VOC testing. Different ways to choose nanomaterial-based sensors are discussed, while considering the profiles of targeted volatile markers and possible limitations of applying the sensing approach. Perspectives for taking volatolomics to a new level in the field of diagnostics are highlighted.

Transformative tools for tackling tuberculosis

The world is in need of more effective approaches to controlling tuberculosis. The development of improved control strategies has been hampered by deficiencies in the tools available for detecting Mycobacterium tuberculosis and defining the dynamic consequences of the interaction of M. tuberculosis with its human host. Key needs include a highly sensitive, specific nonsputum diagnostic; biomarkers predictive of responses to therapy; correlates of risk for disease development; and host response-independent markers of M. tuberculosis infection. Tools able to sensitively detect and quantify total body M. tuberculosis burden might well be transformative across many needed use cases. Here, we review the current state of the field, paying particular attention to needed changes in experimental paradigms that would facilitate the discovery, validation, and development of such tools.

Assessment of terbium (III) as a luminescent probe for the detection of tuberculosis biomarkers

A detection method for nicotinic acid, a specific metabolite marker of Mycobacterium tuberculosis present in cultures and patients' breath, is studied in complex solutions containing other metabolites and in biological media such as urine, saliva and breath condensate. The method is based on the analysis of the luminescence increase of Tb(3+) complexes in the presence of nicotinic acid due to the energy transfer from the excited ligand to the lanthanide ion. It is shown that other potential markers found in M. tuberculosis culture supernatant, such as methyl phenylacetate, p-methyl anisate, methyl nicotinate and 2-methoxy biphenyl, can interfere with nicotinic acid via a competitive absorption of the excitation photons. A new strategy to circumvent these interferences is proposed with an upstream trapping of volatile markers preceding the detection of nicotinic acid in the liquid phase via the luminescence of Tb(3+) complexes. The cost of the method is evaluated and compared with the Xpert MTB/RIF test endorsed by the World Health Organization.

Analysis of Breath Specimens for Biomarkers of Plasmodium falciparum Infection

Currently, the majority of diagnoses of malaria rely on a combination of the patient's clinical presentation and the visualization of parasites on a stained blood film. Breath offers an attractive alternative to blood as the basis for simple, noninvasive diagnosis of infectious diseases. In this study, breath samples were collected from individuals during controlled malaria to determine whether specific malaria-associated volatiles could be detected in breath. We identified 9 compounds whose concentrations varied significantly over the course of malaria: carbon dioxide, isoprene, acetone, benzene, cyclohexanone, and 4 thioethers. The latter group, consisting of allyl methyl sulfide, 1-methylthio-propane, (Z)-1-methylthio-1-propene, and (E)-1-methylthio-1-propene, had not previously been associated with any disease or condition. Before the availability of antimalarial drug treatment, there was evidence of concurrent 48-hour cyclical changes in the levels of both thioethers and parasitemia. When thioether concentrations were subjected to a phase shift of 24 hours, a direct correlation between the parasitemia and volatile levels was revealed. Volatile levels declined monotonically approximately 6.5 hours after initial drug treatment, correlating with clearance of parasitemia. No thioethers were detected in in vitro cultures of Plasmodium falciparum. The metabolic origin of the thioethers is not known, but results suggest that interplay between host and parasite metabolic pathways is involved in the production of these thioethers.

Neglected diseases prioritized in Brazil under the perspective of metabolomics: A review

This review article compiles in a critical manner literature publications regarding seven neglected diseases (ND) prioritized in Brazil (Chagas disease, dengue, leishmaniasis, leprosy, malaria, schistosomiasis, and tuberculosis) under the perspective of metabolomics. Both strategies, targeted and untargeted metabolomics, were considered in the compilation. The majority of studies focused on biomarker discovery for diagnostic purposes, and on the search of novel or alternative therapies against the ND under consideration, although temporal progression of the infection at metabolic level was also addressed. Tuberculosis, followed by schistosomiasis, malaria and leishmaniasis are the diseases that received larger attention in terms of number of publications. Dengue and leprosy were the least studied and Chagas disease received intermediate attention. NMR and HPLC-MS technologies continue to predominate among the analytical platforms of choice in the metabolomic studies of ND. A plethora of metabolites were identified in the compiled studies, with expressive predominancy of amino acids, organic acids, carbohydrates, nucleosides, lipids, fatty acids, and derivatives.

Monolayer-capped gold nanoparticles for disease detection from breath

The recognition of volatile organic compounds in breath samples is a promising approach for noninvasive safe diagnosis of disease. Spectrometry and spectroscopy methods used for breath analysis suffer from suboptimal accuracy, are expensive and are unsuitable for diagnostics. This article presents a concise review on arrays of monolayer-capped gold nanoparticle (GNP) sensors in conjugation with pattern recognition methods for cost-effective, fast and high-throughput point-of-care diagnostic results from exhaled breath samples. The article starts with a general introduction to the rationale and advantages of breath analysis as well as with a presentation of the utility of monolayer-capped GNP sensors in this field. The article continues with a presentation of the main fabrication and operation principles of these GNP sensors and concludes with selected examples regarding their utility in different fields of medicine, particularly in neurology, infectiology, respiratory medicine and oncology.

Fecal Volatile Organic Ccompound Profiles from White-Tailed Deer (Odocoileus virginianus) as Indicators of Mycobacterium bovis Exposure or Mycobacterium bovis Bacille Calmette-Guerin (BCG) Vaccination

White-tailed deer (Odocoileus virginianus) serve as a reservoir for bovine tuberculosis, caused by Mycobacterium bovis, and can be a source of infection in cattle. Vaccination with M. bovis Bacille Calmette Guerin (BCG) is being considered for management of bovine tuberculosis in deer. Presently, no method exists to non-invasively monitor the presence of bovine tuberculosis in deer. In this study, volatile organic compound profiles of BCG-vaccinated and non-vaccinated deer, before and after experimental challenge with M. bovis strain 95–1315, were generated using solid phase microextraction fiber head-space sampling over suspended fecal pellets with analysis by gas chromatography/mass spectrometry. Chromatograms were processed using XCMS Online to characterize ion variation among treatment groups. The principal component scores resulting from significant (α = 0.05) ion responses were used to build linear discriminant analysis models. The sensitivity and specificity of these models were used to evaluate the feasibility of using this analytical approach to distinguish within group comparisons between pre- and post-M. bovis challenge: non-vaccinated male or female deer, BCG-vaccinated male deer, and the mixed gender non-vaccinated deer data. Seventeen compounds were identified in this analysis. The peak areas for these compounds were used to build a linear discriminant classification model based on principal component analysis scores to evaluate the feasibility of discriminating between fecal samples from M. bovis challenged deer, irrespective of vaccination status. The model best representing the data had a sensitivity of 78.6% and a specificity of 91.4%. The fecal head-space sampling approach presented in this pilot study provides a non-invasive method to discriminate between M. bovis challenged deer and BCG-vaccinated deer. Additionally, the technique may prove invaluable for BCG efficacy studies with free-ranging deer as well as for use as a non-invasive monitoring system for the detection of tuberculosis in captive deer and other livestock.

Breath biomarkers of whole-body gamma irradiation in the Göttingen minipig

There is widespread interest in the development of tools to estimate radiation exposures. Exhaled breath provides a novel matrix for assessing biomarkers that could be correlated with exposures. The use of exhaled breath for estimating radiation exposure is warranted, as studies have shown that external exposure to ionizing radiation causes oxidative stress that accelerates lipid peroxidation of polyunsaturated fatty acids, liberating alkanes and alkane metabolites that are excreted in the breath as volatile organic compounds (VOCs). As a proof of principle study, small groups (n = 4) of Göttingen minipigs were whole-body irradiated with gamma rays delivered by a 60Co source at absorbed doses of 0, 0.25, 0.5, 0.75, 1, 1.25, 2, and 4 Gy. Additional groups (n = 4) were treated with lipopolysaccharide (LPS) or granulocyte colony stimulating factor (G-CSF), with and without concurrent 60Co exposure, at an absorbed dose of 1 Gy. Breath and background air VOC samples were collected on days -3, -2, -1, 0 pre-irradiation, then at 0.25, 24, 48, 72, and 168 h post-irradiation. VOCs were analyzed by automated thermal desorption with two-dimensional gas chromatography and time-of-flight mass spectrometry (ATD GCxGC TOF MS). The results show significant changes in 58 breath VOCs post-irradiation, mainly consisting of methylated and other derivatives of alkanes, alkenes, and benzene. Using a multivariate combination of these VOCs, a radiation response function was constructed, which was significantly elevated at 15 min post irradiation and remained elevated throughout the study (to 168 h post irradiation). As a binary test of radiation absorbed doses ≥ 0.25 Gy, the radiation response function distinguished irradiated animals from shams (0 Gy) with 83-84% accuracy. A randomly derived radiation response function was robust: When half of the biomarkers were removed, accuracy was 75%. An optimally derived function with two biomarkers was 82% accurate. As a binary test of radiation absorbed doses ≥ 0.5 Gy, the radiation response function identified irradiated animals with an accuracy of 87% at 15 min post irradiation and 75.5% at 168 h post irradiation. Treatment with LPS and G-CSF did not affect the radiation response function. This proof-of-principle study supports the hypothesis that breath VOCs may be used for estimating radiation exposures. Further studies will be required to validate the sensitivity and specificity of these potential biomarkers.

Diagnosing tuberculosis with a novel support vector machine-based artificial immune recognition system

BACKGROUND

Tuberculosis (TB) is a major global health problem, which has been ranked as the second leading cause of death from an infectious disease worldwide. Diagnosis based on cultured specimens is the reference standard, however results take weeks to process. Scientists are looking for early detection strategies, which remain the cornerstone of tuberculosis control. Consequently there is a need to develop an expert system that helps medical professionals to accurately and quickly diagnose the disease. Artificial Immune Recognition System (AIRS) has been used successfully for diagnosing various diseases. However, little effort has been undertaken to improve its classification accuracy.

OBJECTIVES

In order to increase the classification accuracy of AIRS, this study introduces a new hybrid system that incorporates a support vector machine into AIRS for diagnosing tuberculosis.

PATIENTS AND METHODS

Patient epacris reports obtained from the Pasteur laboratory of Iran were used as the benchmark data set, with the sample size of 175 (114 positive samples for TB and 60 samples in the negative group). The strategy of this study was to ensure representativeness, thus it was important to have an adequate number of instances for both TB and non-TB cases. The classification performance was measured through 10-fold cross-validation, Root Mean Squared Error (RMSE), sensitivity and specificity, Youden's Index, and Area Under the Curve (AUC). Statistical analysis was done using the Waikato Environment for Knowledge Analysis (WEKA), a machine learning program for windows.

RESULTS

With an accuracy of 100%, sensitivity of 100%, specificity of 100%, Youden's Index of 1, Area Under the Curve of 1, and RMSE of 0, the proposed method was able to successfully classify tuberculosis patients.

CONCLUSIONS

There have been many researches that aimed at diagnosing tuberculosis faster and more accurately. Our results described a model for diagnosing tuberculosis with 100% sensitivity and 100% specificity. This model can be used as an additional tool for experts in medicine to diagnose TBC more accurately and quickly.

Microextraction techniques in breath biomarker analysis

Breath volatile organic compound analysis may open a non-invasive window onto (patho)physiological and metabolic processes in the body. Breath tests require controlled sampling with respect to different breath phases and on-site and point-of-care applicability. Microextraction techniques such as solid phase microextraction (SPME) or needle-trap microextraction (NTME) meet these requirements. Small sample volumes and fast and controlled sample preparation combine on-site sampling and pre-concentration in one step. Detection limits in the low ppbV range and fast and simple processing facilitate the application of distribution-based SPME for screening and targeted analysis. Exhaustive NTME has shown further advantages such as fast and automated sampling, improved stability and reproducibility with improved detection limits. Combinations of different sorbents and thermal expansion desorption have shown most promising properties when applied to water saturated breath samples. This article addresses major challenges and advantages of microextraction techniques in breath analysis. Important progress, current applications and future trends are discussed.

Breathomics in lung disease

Volatile organic compounds (VOCs) are produced by virtually all metabolic processes of the body. As such, they have potential to serve as noninvasive metabolic biomarkers. Since exhaled VOCs are either derived from the respiratory tract itself or have passed the lungs from the circulation, they are candidate biomarkers in the diagnosis and monitoring of pulmonary diseases in particular. Good examples of the possibilities of exhaled volatiles in pulmonary medicine are provided by the potential use of VOCs to discriminate between patients with lung cancer and healthy control subjects and to noninvasively diagnose infectious diseases and the association between VOCs and markers of disease activity that has been established in obstructive lung diseases. Several steps are, however, required prior to implementation of breath-based diagnostics in daily clinical practice. First, VOCs should be studied in the intention-to-diagnose population, because biomarkers are likely to be affected by multiple (comorbid) conditions. Second, breath collection and analysis procedures need to be standardized to allow pooling of data. Finally, apart from probabilistic analysis for diagnostic purposes, detailed examination of the nature of volatile biomarkers not only will improve our understanding of the pathophysiologic origins of these markers and the nature of potential confounders but also can enable the development of sensors that exhibit maximum sensitivity and specificity toward specific applications. By adhering to such an approach, exhaled biomarkers can be validated in the diagnosis, monitoring, and treatment of patients in pulmonary medicine and contribute to the development of personalized medicine.

A cross-sectional study of breath acetone based on diabetic metabolic disorders

Breath acetone is a known biomarker for diabetes mellitus in breath analysis. In this work, a cross-sectional study of breath acetone based on clinical metabolic disorders of type 2 diabetes mellitus (T2DM) was carried out. Breath acetone concentrations of 113 T2DM patients and 56 apparently healthy individuals were measured at a single time point. Concentrations varied from 0.22 to 9.41 ppmv (mean 1.75 ppmv) for T2DM, which were significantly higher than those for normal controls (ranged from 0.32 to 1.96 ppmv, mean 0.72 ppmv, p = 0.008). Observations in our work revealed that breath acetone concentrations elevated to different degrees, along with the abnormality of blood glucose, glycated hemoglobin (HbA1c), triglyceride and cholesterol. Breath acetone showed obviously positive correlations with blood ketone and urine ketone. Possible metabolic relations between breath acetone and diabetic disorders were also discussed. This work aimed at giving an overall assessment of breath acetone from the perspective of clinical parameters for type 2 diabetes.

Breath analysis as a potential and non-invasive frontier in disease diagnosis: an overview

Currently, a small number of diseases, particularly cardiovascular (CVDs), oncologic (ODs), neurodegenerative (NDDs), chronic respiratory diseases, as well as diabetes, form a severe burden to most of the countries worldwide. Hence, there is an urgent need for development of efficient diagnostic tools, particularly those enabling reliable detection of diseases, at their early stages, preferably using non-invasive approaches. Breath analysis is a non-invasive approach relying only on the characterisation of volatile composition of the exhaled breath (EB) that in turn reflects the volatile composition of the bloodstream and airways and therefore the status and condition of the whole organism metabolism. Advanced sampling procedures (solid-phase and needle traps microextraction) coupled with modern analytical technologies (proton transfer reaction mass spectrometry, selected ion flow tube mass spectrometry, ion mobility spectrometry, e-noses, etc.) allow the characterisation of EB composition to an unprecedented level. However, a key challenge in EB analysis is the proper statistical analysis and interpretation of the large and heterogeneous datasets obtained from EB research. There is no standard statistical framework/protocol yet available in literature that can be used for EB data analysis towards discovery of biomarkers for use in a typical clinical setup. Nevertheless, EB analysis has immense potential towards development of biomarkers for the early disease diagnosis of diseases.

A rapid method for breath analysis in cystic fibrosis patients

For easy handling and speed of lung diseases diagnostics, approaches based on volatile organic compounds (VOCs), including those emitted by pathogenic microorganisms, are considered but currently require considerable sampling efforts. We tested whether easy-to-handle and fast detection of lung infections is possible using solid-phase microextraction (SPME) of 100 ml of exhaled breath. An analytical procedure for the detection of VOCs from the headspace of epithelial lung cells infected with four human pathogens was developed. The feasibility of this method was tested in a cystic fibrosis (CF) outpatient clinic in vivo. Exhaled breath was extracted by SPME and analyzed by gas chromatography-mass spectrometry (GC-MS). The compositions of VOCs released in the infection model were characteristic for all individual pathogens tested. Exhaled breath of CF patients allowed clear distinction of CF patients and controls by their VOC compositions using multivariate analyses. Interestingly, the major specific VOCs detected in the exhaled breath of infected CF patients in vivo differed from those monitored during bacterial in vitro growth. SPME extraction of VOCs from 100 ml of human breath allowed the distinction between CF patients and healthy probands. Our results highlight the importance of assessing the entire pattern of VOCs instead of selected biomarkers for diagnostic purposes, as well as the need to use clinical samples to identify reliable biomarkers. This study provides the proof-of-concept for the approach using the composition of exhaled VOCs in human breath for the rapid identification of infectious agents in patients with lower respiratory tract infections.

Chemical analysis of whale breath volatiles: a case study for non-invasive field health diagnostics of marine mammals

We explored the feasibility of collecting exhaled breath from a moribund gray whale (Eschrichtius robustus) for potential non-invasive health monitoring of marine mammals. Biogenic volatile organic compound (VOC) profiling is a relatively new field of research, in which the chemical composition of breath is used to non-invasively assess the health and physiological processes on-going within an animal or human. In this study, two telescopic sampling poles were designed and tested with the primary aim of collecting whale breath exhalations (WBEs). Once the WBEs were successfully collected, they were immediately transferred onto a stable matrix sorbent through a custom manifold system. A total of two large volume WBEs were successfully captured and pre-concentrated onto two Tenax^®-TA traps (one exhalation per trap). The samples were then returned to the laboratory where they were analyzed using solid phase micro extraction (SPME) and gas chromatography/mass spectrometry (GC/MS). A total of 70 chemicals were identified (58 positively identified) in the whale breath samples. These chemicals were also matched against a database of VOCs found in humans, and 44% of chemicals found in the whale breath are also released by healthy humans. The exhaled gray whale breath showed a rich diversity of chemicals, indicating the analysis of whale breath exhalations is a promising new field of research.

Taking your breath away: metabolomics breathes life in to personalized medicine

Breath-based metabolomics (breathomics) is an exciting developing area of biotechnology that centers on the capture, identification, and quantification of volatile organic compound (VOC) patterns in human breath and their utilization as tools in the diagnosis of a broad spectrum of medical problems. With the age of personalized medicines demanding rapid bespoke diagnosis and treatment, this area of molecular diagnostics is beginning to see an upsurge in biotechnological advancement. Here, we discuss recent improvements and directions in the development of breath VOC analysis and diagnosis platforms that offer the potential for disease biomarker discovery and disease prognosis.

Rapid diagnosis of TB using GC-MS and chemometrics

The search continues for a rapid diagnostic test for TB that has high sensitivity and specificity and is useable in sophisticated environments and in deprived regions with poor infrastructure. We discuss here the modern bioanalytical techniques that can be used to discover biomarkers of infection with Mycobacterium tuberculosis, focusing on techniques using GC. We will also discuss the use of GC-MS to identify volatile organic compounds in the headspace of bacterial culture or in samples of breath, serum or urine. Biomarkers discovered in the 'clean' environment of culture may differ from those in patients. A number of biomarkers have been found in patients, with little consistency in the various studies to date. Reproducibility is difficult; the impressive results found initially with a few patients are rarely repeatable when a larger sample series is tested. Mycobacterial lipids offer promise for distinguishing M. tuberculosis from nontuberculous mycobacteria directly in sputum.

The human volatilome: volatile organic compounds (VOCs) in exhaled breath, skin emanations, urine, feces and saliva

Breath analysis is a young field of research with its roots in antiquity. Antoine Lavoisier discovered carbon dioxide in exhaled breath during the period 1777-1783, Wilhelm (Vilém) Petters discovered acetone in breath in 1857 and Johannes Müller reported the first quantitative measurements of acetone in 1898. A recent review reported 1765 volatile compounds appearing in exhaled breath, skin emanations, urine, saliva, human breast milk, blood and feces. For a large number of compounds, real-time analysis of exhaled breath or skin emanations has been performed, e.g., during exertion of effort on a stationary bicycle or during sleep. Volatile compounds in exhaled breath, which record historical exposure, are called the 'exposome'. Changes in biogenic volatile organic compound concentrations can be used to mirror metabolic or (patho)physiological processes in the whole body or blood concentrations of drugs (e.g. propofol) in clinical settings-even during artificial ventilation or during surgery. Also compounds released by bacterial strains like Pseudomonas aeruginosa or Streptococcus pneumonia could be very interesting. Methyl methacrylate (CAS 80-62-6), for example, was observed in the headspace of Streptococcus pneumonia in concentrations up to 1420 ppb. Fecal volatiles have been implicated in differentiating certain infectious bowel diseases such as Clostridium difficile, Campylobacter, Salmonella and Cholera. They have also been used to differentiate other non-infectious conditions such as irritable bowel syndrome and inflammatory bowel disease. In addition, alterations in urine volatiles have been used to detect urinary tract infections, bladder, prostate and other cancers. Peroxidation of lipids and other biomolecules by reactive oxygen species produce volatile compounds like ethane and 1-pentane. Noninvasive detection and therapeutic monitoring of oxidative stress would be highly desirable in autoimmunological, neurological, inflammatory diseases and cancer, but also during surgery and in intensive care units. The investigation of cell cultures opens up new possibilities for elucidation of the biochemical background of volatile compounds. In future studies, combined investigations of a particular compound with regard to human matrices such as breath, urine, saliva and cell culture investigations will lead to novel scientific progress in the field.

Molecular approaches and biomarkers for detection of Mycobacterium tuberculosis

Tuberculosis (TB) continues to be a public health emergency, compounded by the lack of adequate diagnostic testing in many regions of the world. New advances in the molecular detection of Mycobacterium tuberculosis, including faster and simpler nucleic acid amplification tests, have resulted in rapid and cost-effective methods to diagnose TB and test for drug resistance. Ongoing research on biomarkers for TB infection may lead to new tests for blood, urine, breath, and sputum. Sustained investment in the development and dissemination of diagnostic tests for TB is critical for increasing TB case finding, placing patients on appropriate treatment, and reducing transmission.

Rapid point-of-care breath test for biomarkers of breast cancer and abnormal mammograms

Background

Previous studies have reported volatile organic compounds (VOCs) in breath as biomarkers of breast cancer and abnormal mammograms, apparently resulting from increased oxidative stress and cytochrome p450 induction. We evaluated a six-minute point-of-care breath test for VOC biomarkers in women screened for breast cancer at centers in the USA and the Netherlands.

Methods

244 women had a screening mammogram (93/37 normal/abnormal) or a breast biopsy (cancer/no cancer 35/79). A mobile point-of-care system collected and concentrated breath and air VOCs for analysis with gas chromatography and surface acoustic wave detection. Chromatograms were segmented into a time series of alveolar gradients (breath minus room air). Segmental alveolar gradients were ranked as candidate biomarkers by C-statistic value (area under curve [AUC] of receiver operating characteristic [ROC] curve). Multivariate predictive algorithms were constructed employing significant biomarkers identified with multiple Monte Carlo simulations and cross validated with a leave-one-out (LOO) procedure.

Results

Performance of breath biomarker algorithms was determined in three groups: breast cancer on biopsy versus normal screening mammograms (81.8% sensitivity, 70.0% specificity, accuracy 79% (73% on LOO) [C-statistic value], negative predictive value 99.9%); normal versus abnormal screening mammograms (86.5% sensitivity, 66.7% specificity, accuracy 83%, 62% on LOO); and cancer versus no cancer on breast biopsy (75.8% sensitivity, 74.0% specificity, accuracy 78%, 67% on LOO).

Conclusions

A pilot study of a six-minute point-of-care breath test for volatile biomarkers accurately identified women with breast cancer and with abnormal mammograms. Breath testing could potentially reduce the number of needless mammograms without loss of diagnostic sensitivity.

A pilot study exploring the use of breath analysis to differentiate healthy cattle from cattle experimentally infected with Mycobacterium bovis

Bovine tuberculosis, caused by Mycobacterium bovis, is a zoonotic disease of international public health importance. Ante-mortem surveillance is essential for control; however, current surveillance tests are hampered by limitations affecting ease of use or quality of results. There is an emerging interest in human and veterinary medicine in diagnosing disease via identification of volatile organic compounds produced by pathogens and host-pathogen interactions. The objective of this pilot study was to explore application of existing human breath collection and analysis methodologies to cattle as a means to identify M. bovis infection through detection of unique volatile organic compounds or changes in the volatile organic compound profiles present in breath. Breath samples from 23 male Holstein calves (7 non-infected and 16 M. bovis-infected) were collected onto commercially available sorbent cartridges using a mask system at 90 days post-inoculation with M. bovis. Samples were analyzed using gas chromatography-mass spectrometry, and chromatographic data were analyzed using standard analytical chemical and metabolomic analyses, principle components analysis, and a linear discriminant algorithm. The findings provide proof of concept that breath-derived volatile organic compound analysis can be used to differentiate between healthy and M. bovis-infected cattle.

Exhaled breath analysis by electronic nose in airways disease. Established issues and key questions

Exhaled air contains many volatile organic compounds (VOCs) that are the result of normal and disease-associated metabolic processes anywhere in the body. Different omics techniques can assess the pattern of these VOCs. One such omics technique suitable for breath analysis is represented by electronic noses (eNoses), providing fingerprints of the exhaled VOCs, called breathprints. Breathprints have been shown to be altered in different disease states, including in asthma and COPD. This review describes the current status on clinical validation and application of breath analysis by electronic noses in the diagnosis and monitoring of chronic airways diseases. Furthermore, important methodological issues including breath sampling, modulating factors and incompatibility between eNoses are raised and discussed. Next steps towards clinical application of electronic noses are provided, including further validation in suspected disease, assessment of the influence of different comorbidities, the value in longitudinal monitoring of patients with asthma and COPD and the possibility to predict treatment responses. Eventually, a Breath Cloud may be constructed, a large database containing disease-specific breathprints. When collaborative efforts are put into optimization of this technique, it can provide a rapid and non-invasive first line diagnostic test.

Clinical application of volatile organic compound analysis for detecting infectious diseases

This review article introduces the significance of testing of volatile organic compounds (VOCs) in clinical samples and summarizes important features of some of the technologies. Compared to other human diseases such as cancer, studies on VOC analysis in cases of infectious diseases are limited. Here, we have described results of studies which have used some of the appropriate technologies to evaluate VOC biomarkers and biomarker profiles associated with infections. The publications reviewed include important infections of the respiratory tract, gastrointestinal tract, urinary tract, and nasal cavity. The results highlight the use of VOC biomarker profiles resulting from certain infectious diseases in discriminating between infected and healthy subjects. Infection-related VOC profiles measured in exhaled breath as well as from headspaces of feces or urine samples are a source of information with respect to disease detection. The volatiles emitted in clinical matrices may on the one hand represent metabolites of the infecting pathogen or on the other hand reflect pathogen-induced host responses or, indeed, a combination of both. Because exhaled-breath samples are easy to collect and online instruments are commercially available, VOC analysis in exhaled breath appears to be a promising tool for noninvasive detection and monitoring of infectious diseases.

Tuberculosis disease diagnosis using artificial immune recognition system

BACKGROUND

There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods.

OBJECTIVES

This study is aimed at diagnosing TB using hybrid machine learning approaches.

MATERIALS AND METHODS

Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporating a fuzzy logic controller and artificial immune recognition system. The features are normalized through a fuzzy rule based on a labeling system. The labeled features are categorized into normal and tuberculosis classes using the Artificial Immune Recognition Algorithm.

RESULTS

Overall, the highest classification accuracy reached was for the 0.8 learning rate (α) values. The artificial immune recognition system (AIRS) classification approaches using fuzzy logic also yielded better diagnosis results in terms of detection accuracy compared to other empirical methods. Classification accuracy was 99.14%, sensitivity 87.00%, and specificity 86.12%.

Nanomaterial-based sensors for detection of disease by volatile organic compounds

The importance of developing new diagnostic and detection technologies for the growing number of clinical challenges is rising each year. Here, we present a concise, yet didactic review on a new diagnostics frontier based on the detection of disease-related volatile organic compounds (VOCs) by means of nanomaterial-based sensors. Nanomaterials are ideal for such sensor arrays because they are easily fabricated, chemically versatile and can be integrated into currently available sensing platforms. Following a general introduction, we provide a brief description of the VOC-related diseases concept. Then, we focus on detection of VOC-related diseases by selective and crossreactive sensing approaches, through chemical, optical and mechanical transducers incorporating the most important classes of nanomaterials. Selected examples of the integration of nanomaterials into selective sensors and crossreactive sensor arrays are given. We conclude with a brief discussion on the integration possibilities of different types of nanomaterials into sensor arrays, and the expected outcomes and limitations.

Volatile emissions from Mycobacterium avium subsp. paratuberculosis mirror bacterial growth and enable distinction of different strains

Control of paratuberculosis in livestock is hampered by the low sensitivity of established direct and indirect diagnostic methods. Like other bacteria, Mycobacterium avium subsp. paratuberculosis (MAP) emits volatile organic compounds (VOCs). Differences of VOC patterns in breath and feces of infected and not infected animals were described in first pilot experiments but detailed information on potential marker substances is missing. This study was intended to look for characteristic volatile substances in the headspace of cultures of different MAP strains and to find out how the emission of VOCs was affected by density of bacterial growth. One laboratory adapted and four field strains, three of MAP C-type and one MAP S-type were cultivated on Herrold’s egg yolk medium in dilutions of 10^-0, 10^-2, 10^-4 and 10^-6. Volatile substances were pre-concentrated from the headspace over the MAP cultures by means of Solid Phase Micro Extraction (SPME), thermally desorbed from the SPME fibers and separated and identified by means of GC-MS. Out of the large number of compounds found in the headspace over MAP cultures, 34 volatile marker substances could be identified as potential biomarkers for growth and metabolic activity. All five MAP strains could clearly be distinguished from blank culture media by means of emission patterns based on these 34 substances. In addition, patterns of volatiles emitted by the reference strain were significantly different from the field strains. Headspace concentrations of 2-ethylfuran, 2-methylfuran, 3-methylfuran, 2-pentylfuran, ethyl acetate, 1-methyl-1-H-pyrrole and dimethyldisulfide varied with density of bacterial growth. Analysis of VOCs emitted from mycobacterial cultures can be used to identify bacterial growth and, in addition, to differentiate between different bacterial strains. VOC emission patterns may be used to approximate bacterial growth density. In a perspective volatile marker substances could be used to diagnose MAP infections in animals and to identify different bacterial strains and origins.

Detection of an extended human volatome with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry

BACKGROUND

Comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GCxGC-TOF MS) has been proposed as a powerful new tool for multidimensional analysis of complex chemical mixtures. We investigated GCxGC-TOF MS as a new method for identifying volatile organic compounds (VOCs) in normal human breath.

METHODS

Samples of alveolar breath VOCs and ambient room air VOC were collected with a breath collection apparatus (BCA) onto separate sorbent traps from 34 normal healthy volunteers (mean age = 40 yr, SD = 17 yr, male/female = 19/15). VOCs were separated on two serial capillary columns separated by a cryogenic modulator, and detected with TOF MS. The first and second dimension columns were non-polar and polar respectively.

RESULTS

BCA collection combined with GC×GC-TOF MS analysis identified approximately 2000 different VOCs in samples of human breath, many of which have not been previously reported. The 50 VOCs with the highest alveolar gradients (abundance in breath minus abundance in ambient room air) mostly comprised benzene derivatives, acetone, methylated derivatives of alkanes, and isoprene.

CONCLUSIONS

Collection and analysis of breath VOCs with the BCA-GC×GC-TOF MS system extended the size of the detectable human volatile metabolome, the volatome, by an order of magnitude compared to previous reports employing one-dimensional GC-MS. The size of the human volatome has been under-estimated in the past due to coelution of VOCs in one-dimensional GC analytical systems.

Breath tests in respiratory and critical care medicine: from research to practice in current perspectives

Today, exhaled nitric oxide has been studied the most, and most researches have now focused on asthma. More than a thousand different volatile organic compounds have been observed in low concentrations in normal human breath. Alkanes and methylalkanes, the majority of breath volatile organic compounds, have been increasingly used by physicians as a novel method to diagnose many diseases without discomforts of invasive procedures. None of the individual exhaled volatile organic compound alone is specific for disease. Exhaled breath analysis techniques may be available to diagnose and monitor the diseases in home setting when their sensitivity and specificity are improved in the future.

Detection of volatile organic compounds as biomarkers in breath analysis by different analytical techniques

Breath is a rich mixture containing numerous volatile organic compounds at trace amounts (ppbv–pptv level) such as: hydrocarbons, alcohols, ketones, aldehydes, esters or heterocycles. The presence of some of them depends on health status. Therefore, breath analysis might be useful for clinical diagnostics, therapy monitoring and control of metabolic or biochemical cell cycle products. This Review presents an update on the latest developments in breath analysis applied to diagnosing different diseases with the help of high-quality equipment. Efforts were made to fully and accurately describe traditional and modern techniques used to determine the components of breath. The techniques were compared in terms of design, function and also detection limit of different volatile organic compounds. GC with different detectors, MS, optical sensor and laser spectroscopic detection techniques are also discussed.

Diagnostic potential of the pulsed discharged helium ionization detector (PDHID) for pathogenic Mycobacterial volatile biomarkers

Pathogenic Mycobacteria cause diseases in animals and humans with significant economic and societal consequences. Current methods for Mycobacterial detection relies upon time- and labor-intensive techniques such as culturing or DNA analysis. Using gas chromatography and mass spectrometry, four volatile compounds (methyl phenylacetate, methyl p-anisate, methyl nicotinate and o-phenyl anisole) were recently proposed as potential biomarkers for Mycobacteria. We demonstrate for the first time the capabilities of a field-deployable, pulsed discharge helium ionization detector (PDHID) for sensing these volatiles. We determined the analytical performance of the PDHID toward these Mycobacterial volatiles. Detector performance was moderately affected over the temperature range of 150 to 350 °C. The linear dynamic range for all four analytes exceeded three orders of magnitude. The limits of detection (LOD) and quantitation (LOQ) were calculated as 150 and 450 pg respectively, for all compounds, except methyl phenylacetate (LOD and LOQ, 90 and 270 pg, respectively). Control charts revealed that the PDHID detection system was generally stable, and deviations could be traced to common causes and excluded special causes. Grob tests and ionization potential data suggest that the PDHID is capable of detecting Mycobacterial volatiles in a complex milieu such as culture headspace or breath samples from tuberculosis patients. The diagnostic potential of the PDHID is critical to our goal of a handheld, field-deployable 'sniffer' system for biological pathogens and chemical warfare agents.

Robust detection of P. aeruginosa and S. aureus acute lung infections by secondary electrospray ionization-mass spectrometry (SESI-MS) breathprinting: from initial infection to clearance

Before breath-based diagnostics for lung infections can be implemented in the clinic, it is necessary to understand how the breath volatiles change during the course of infection, and ideally, to identify a core set of breath markers that can be used to diagnose the pathogen at any point during the infection. In the study presented here, we use secondary electrospray ionization-mass spectrometry (SESI-MS) to characterize the breathprint of Pseudomonas aeruginosa and Staphylococcus aureus lung infections in a murine model over a period of 120 h, with a total of 86 mice in the study. Using partial least squares-discriminant analysis (PLS-DA) to evaluate the time-course data, we were able to show that SESI-MS breathprinting can be used to robustly classify acute P. aeruginosa and S. aureus mouse lung infections at any time during the 120 h infection/clearance process. The variable importance plot from PLS indicates that multiple peaks from the SESI-MS breathprints are required for discriminating the bacterial infections. Therefore, by utilizing the entire breathprint rather than single biomarkers, infectious agents can be diagnosed by SESI-MS independent of when during the infection breath is tested.

Monitoring states of altered carbohydrate metabolism via breath analysis: are times ripe for transition from potential to reality?

PURPOSE OF REVIEW

To introduce the potential of breath analysis as a diagnostic or monitoring tool in diabetes.

RECENT FINDINGS

Blood testing for plasma glucose and other metabolic variables is the base for the diagnosis and management of diabetes, whose two main types (type 1 and type 2, T1DM, T2DM) are projected to affect 450 million by 2030. As blood testing is often uncomfortable, painful, costly, and in some situations unreliable, the quest for alternative, noninvasive methods has been ongoing for decades. Breath analysis has emerged as an ideal alternative as sample collection is easy, painless, flexible, noninvasive, practical, and inexpensive. No single exhaled gas can reflect systemic glucose concentrations. Multiple gases, however, have been linked to various aspects of glucose metabolism, and integrated analysis of their simultaneous profiles during prolonged glycemic fluctuations has yielded accurate predictions of plasma values, building expectation that a clinically usable breath-based glucometer may be developed within a few years.

SUMMARY

While prototypes of hand-held breath testing glucometers may still be several years away, current research shows the imminent promise of this methodology and the widening support for its development.

Detection of volatile biomarkers of therapeutic radiation in breath

Breath testing could provide a rational tool for radiation biodosimetry because radiation causes distinct stress-producing molecular damage, notably an increased production of reactive oxygen species. The resulting oxidative stress accelerates lipid peroxidation of polyunsaturated fatty acids, liberating alkanes and alkane metabolites that are excreted in the breath as volatile organic compounds (VOCs). Breath tests were performed before and after radiation therapy over five days in 31 subjects receiving daily fractionated doses: 180-400 cGy d(-1) standard radiotherapy (n = 26), or 700-1200 cGy d(-1) high-dose stereotactic body radiotherapy (n = 5). Breath VOCs were assayed using comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry. Multiple Monte Carlo simulations identified approximately 50 VOCs as greater-than-chance biomarkers of radiation on all five days of the study. A consistent subset of 15 VOCs was observed at all time points. A radiation response function was built by combining these biomarkers and the resulting dose-effect curve was significantly elevated at all exposures ⩾1.8 Gy. Cross-validated binary algorithms identified radiation exposures ⩾1.8 Gy with 99% accuracy, and ⩾5 Gy with 78% accuracy. In this proof of principal study of breath VOCs, we built a preliminary radiation response function based on 15 VOCs that appears to identify exposure to localized doses of 1.8 Gy and higher. VOC breath testing could provide a new tool for rapid and non-invasive radiation biodosimetry.

Developments in novel breath tests for bacterial and fungal pulmonary infection

PURPOSE OF REVIEW

Breath testing has developed over the last 20 years. New techniques that can identify fingerprints for specific diseases and specific markers of respiratory pathogens have been applied to breath analysis. This review discusses the recent advances in breath analysis for the diagnosis of bacterial and fungal lower respiratory tract infections.

RECENT FINDINGS

The current techniques continue to develop rapidly, but preconcentration techniques are needed to analyse many target volatile organic compounds for most systems. Breath testing with an electronic nose is promising for the diagnosis of tuberculosis (TB), and specific volatiles identifiable by gas chromatography with mass spectrometry have been identified in breath for Mycobacterium tuberculosis, Pseudomonas aeruginosa and Aspergillus fumigatus, but are found at very low concentrations in breath. Contamination from the environment is an ongoing confounding influence. Exhaled breath condensate (EBC) is disappointing as a diagnostic sample.

SUMMARY

Careful attention needs to be paid to the sensitivity and specificity of a technique and confounding from the environment. The role of technologies such as selected ion flow tube-mass spectrometry is emerging. The electronic nose requires further validation for TB. The identification of specific microbial biomarkers aids the quest for improved accuracy. EBC is currently of limited value.

Secondary electrospray ionization-mass spectrometry (SESI-MS) breathprinting of multiple bacterial lung pathogens, a mouse model study

Bacterial pneumonia is one of the leading causes of disease-related morbidity and mortality in the world, in part because the diagnostic tools for pneumonia are slow and ineffective. To improve the diagnosis success rates and treatment outcomes for bacterial lung infections, we are exploring the use of secondary electrospray ionization-mass spectrometry (SESI-MS) breath analysis as a rapid, noninvasive method for determining the etiology of lung infections in situ. Using a murine lung infection model, we demonstrate that SESI-MS breathprints can be used to distinguish mice that are infected with one of seven lung pathogens: Haemophilus influenzae, Klebsiella pneumoniae, Legionella pneumophila, Moraxella catarrhalis, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pneumoniae, representing the primary causes of bacterial pneumonia worldwide. After applying principal components analysis, we observed that with the first three principal components (primarily comprised of data from 14 peaks), all infections were separable via SESI-MS breathprinting (P < 0.0001). Therefore, we have shown the potential of this SESI-MS approach for rapidly detecting and identifying acute bacterial lung infections in situ via breath analysis.

Volatile breath biomarkers for patient monitoring during haemodialysis

Patients with end-stage renal disease (ESRD) are at risk for a numerous complications. This study was intended to evaluate breath analysis for monitoring and therapy initiation under haemodialysis (HD). Exhaled alveolar air from 30 ESRD patients during 4 h thrice-weekly HD was analysed by means of HS-SPME-GC-MS. Venous blood samples were taken for determination of conventional serum parameters. Exhaled concentrations of isoprene (10-589 ppbV) were dropped at initiation of HD and increased at the end of HD. Isoprene concentration changes were similar to changes of serum LDH activities. Variation of exhaled acetone concentrations (59 to 8509 ppbV) was significantly lower in diabetic patients when compared to non-diabetics. Exhaled pentane (0.3 to 12 ppbV) increased at onset of HD and returned to baseline levels afterwards. Benzene concentrations showed typical washout characteristics. Ethanol and DMS concentrations remained constant during HD. Breath analysis can be used to recognize oxidative stress, metabolic conditions and haemolysis during HD. Hence, non-invasive breath testing could be used to monitor ESRD patients under HD and prevent them from being affected by well-known detrimental side effects of renal replacement therapy.

Promising directions in the diagnosis of childhood tuberculosis

Estimates of the burden of childhood tuberculosis have been hampered by the lack of a reliable diagnostic test. Clinical scoring systems, radiological findings and tuberculin skin testing (the traditional methods used for diagnosis) are unreliable, particularly in the era of HIV. Microbiologic confirmation using induced sputum is feasible and has become increasingly important to define the burden of disease and to enable appropriate treatment. The availability of a rapid molecular diagnostic test (Xpert® MTB/RIF; Cepheid) is an important advance that can improve case detection in children and enable rapid detection of mycobacterial drug resistance. Xpert testing of two induced sputum specimens detected approximately 75% of children with culture-confirmed disease. Urine lipoarabinomannan has shown promise as a rapid diagnostic in a subgroup of HIV-infected severely immunocompromised adults, but there have been no data in children so far. Further research is needed to develop a rapid point-of-care, reliable and affordable diagnostic test for childhood tuberculosis that can be widely used.

Overcoming the challenges of studying conservation physiology in large whales: a review of available methods

Large whales are subjected to a variety of conservation pressures that could be better monitored and managed if physiological information could be gathered readily from free-swimming whales. However, traditional approaches to studying physiology have been impractical for large whales, because there is no routine method for capture of the largest species and there is presently no practical method of obtaining blood samples from free-swimming whales. We review the currently available techniques for gathering physiological information on large whales using a variety of non-lethal and minimally invasive (or non-invasive) sample matrices. We focus on methods that should produce information relevant to conservation physiology, e.g. measures relevant to stress physiology, reproductive status, nutritional status, immune response, health, and disease. The following four types of samples are discussed: faecal samples, respiratory samples ('blow'), skin/blubber samples, and photographs. Faecal samples have historically been used for diet analysis but increasingly are also used for hormonal analyses, as well as for assessment of exposure to toxins, pollutants, and parasites. Blow samples contain many hormones as well as respiratory microbes, a diverse array of metabolites, and a variety of immune-related substances. Biopsy dart samples are widely used for genetic, contaminant, and fatty-acid analyses and are now being used for endocrine studies along with proteomic and transcriptomic approaches. Photographic analyses have benefited from recently developed quantitative techniques allowing assessment of skin condition, ectoparasite load, and nutritional status, along with wounds and scars from ship strikes and fishing gear entanglement. Field application of these techniques has the potential to improve our understanding of the physiology of large whales greatly, better enabling assessment of the relative impacts of many anthropogenic and ecological pressures.

Effect of transportation and storage using sorbent tubes of exhaled breath samples on diagnostic accuracy of electronic nose analysis

Many (multi-centre) breath-analysis studies require transport and storage of samples. We aimed to test the effect of transportation and storage using sorbent tubes of exhaled breath samples for diagnostic accuracy of eNose and GC-MS analysis. As a reference standard for diagnostic accuracy, breath samples of asthmatic patients and healthy controls were analysed by three eNose devices. Samples were analysed by GC-MS and eNose after 1, 7 and 14 days of transportation and storage using sorbent tubes. The diagnostic accuracy for eNose and GC-MS after storage was compared to the reference standard. As a validation, the stability was assessed of 15 compounds known to be related to asthma, abundant in breath or related to sampling and analysis. The reference test discriminated asthma and healthy controls with a median AUC (range) of 0.77 (0.72-0.76). Similar accuracies were achieved at t1 (AUC eNose 0.78; GC-MS 0.84), t7 (AUC eNose 0.76; GC-MS 0.79) and t14 (AUC eNose 0.83; GC-MS 0.84). The GC-MS analysis of compounds showed an adequate stability for all 15 compounds during the 14 day period. Short-term transportation and storage using sorbent tubes of breath samples does not influence the diagnostic accuracy for discrimination between asthma and health by eNose and GC-MS.

Clinical use of exhaled volatile organic compounds in pulmonary diseases: a systematic review

There is an increasing interest in the potential of exhaled biomarkers, such as volatile organic compounds (VOCs), to improve accurate diagnoses and management decisions in pulmonary diseases. The objective of this manuscript is to systematically review the current knowledge on exhaled VOCs with respect to their potential clinical use in asthma, lung cancer, chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF), and respiratory tract infections. A systematic literature search was performed in PubMed, EMBASE, Cochrane database, and reference lists of retrieved studies. Controlled, clinical, English-language studies exploring the diagnostic and monitoring value of VOCs in asthma, COPD, CF, lung cancer and respiratory tract infections were included. Data on study design, setting, participant characteristics, VOCs techniques, and outcome measures were extracted. Seventy-three studies were included, counting in total 3,952 patients and 2,973 healthy controls. The collection and analysis of exhaled VOCs is non-invasive and could be easily applied in the broad range of patients, including subjects with severe disease and children. Various research groups demonstrated that VOCs profiles could accurately distinguish patients with a pulmonary disease from healthy controls. Pulmonary diseases seem to be characterized by a disease specific breath-print, as distinct profiles were found in patients with dissimilar diseases. The heterogeneity of studies challenged the inter-laboratory comparability. In conclusion, profiles of VOCs are potentially able to accurately diagnose various pulmonary diseases. Despite these promising findings, multiple challenges such as further standardization and validation of the diverse techniques need to be mastered before VOCs can be applied into clinical practice.

The dual role of biomarkers for understanding basic principles and devising novel intervention strategies in tuberculosis

There is great need for better control measures for tuberculosis (TB). High-throughput analyses, such as transcriptomic and metabolic profiling, offer a promising path toward clinically useful biosignatures. With the help of biomarkers, it will be possible not only to reliably perform diagnosis but also to gain a better understanding of the disease process and, in the future, even predict the onset of disease in infected individuals. Biomarkers based on transcriptomic and metabolic profiles as well as on cytokine composition provide important insights into the basic biological principles of TB and give an opportunity to reliably distinguish TB patients from healthy individuals. Use of biomarkers for point-of-care diagnosis, however, is still a distant goal, which to achieve will require extensive analysis of TB biosignatures across different cohorts and a combination of different platforms.

The clinical potential of exhaled breath analysis for diabetes mellitus

Various compounds in present human breath have long been loosely associated with pathological states (including acetone smell in uncontrolled diabetes). Only recently, however, the precise measurement of exhaled volatile organic compounds (VOCs) and aerosolized particles was made possible at extremely low concentrations by advances in several analytical methodologies, described in detail in the international literature and each suitable for specific subsets of exhaled compounds. Exhaled gases may be generated endogenously (in the pulmonary tract, blood, or peripheral tissues), as metabolic by-products of human cells or colonizing micro-organisms, or may be inhaled as atmospheric pollutants; growing evidence indicates that several of these molecules have distinct cell-to-cell signaling functions. Independent of origin and physiological role, exhaled VOCs are attractive candidates as biomarkers of cellular activity/metabolism, and could be incorporated in future non-invasive clinical testing devices. Indeed, several recent studies reported altered exhaled gas profiles in dysmetabolic conditions and relatively accurate predictions of glucose concentrations, at least in controlled experimental conditions, for healthy and diabetic subjects over a broad range of glycemic values. Optimization of this methodology and validation in large-scale trials under a wider range of conditions is needed to determine its true potential to transition into practical clinical use.