Quantification of volatile metabolites in exhaled breath by selected ion flow tube mass spectrometry, SIFT-MS

Volatile organic compounds (VOCs) detection for the identification of bacterial infections in clinical wound samples

Early detection of wound infections is critical for timely intervention and prevention of possible complications since prompt treatment can help lower pathogen spread and enhance faster healing. Early detection also helps reduce the risk of serious infections requiring extensive medical interventions or life-threatening diseases such as sepsis. Culture-based approaches currently used for bacterial identification have limited sensitivity and specificity. At the same time, they are time-consuming, resulting in delays in therapy and, therefore, having a negative impact on the treatment outcomes. Quantifying the volatile organic compounds (VOCs) released by bacteria residing in wounds is a promising, non-invasive option for detecting infections at early stages. This method allows for continuous monitoring without requiring invasive procedures, thereby reducing patient discomfort and the risk of further complications. Spectroscopy methods and sensors are the primary VOC detection and quantification approaches, but sensors are more rapid, cost-effective, non-invasive, and precise. This review highlights the significance of the early detection of wound infection to enable timely intervention and prevent complications, emphasizing the limitations of culture-based approaches. It also explores the potential of quantifying VOCs using different methods and discusses the correlation between their levels and the rate of bacterial infections in wounds. Additionally, the review evaluates current VOC-based monitoring methods for wound management, identifies gaps in the field, and advocates for further research to advance wound care and enhance patient outcomes.

An optical sensor for ppb-level exhaled acetone detection based on UV-DOAS and spectral upscaling

The method of detecting acetone levels in breath presents a promising approach for monitoring diabetes mellitus (DM). Consequently, the detection of acetone in exhaled breath is garnering significant attention. However, using ultraviolet differential optical absorption spectroscopy (UV-DOAS) for detection of the exhaled acetone has rarely been proposed due to the complex composition of exhaled gases and the baseline drift caused by the acetone absorption feature. In this study, we present an optical sensor based on an improved UV-DOAS and spectral upgrading, enabling the detection of exhaled acetone in the sub-200 nm wavelength band for the first time. Firstly, the overall fitting process in the UV-DOAS was improved to segmental fitting to address the issue of baseline drift, resulting in a standard differential absorption spectrum for acetone. Secondly, a spectral upscaling concentration inversion method based on wavelet coefficient matrix is proposed. This helps effectively handle spectral overlaps among oxygen (O2), ammonia (NH3), and acetone through the additional time-frequency information provided by spectral upscaling. Laboratory-based results demonstrate that our sensor achieves a detection limit of 14.97 ppb∗m, representing exceptional performances. Tests on human exhaled breath samples revealed that the sensor can detect acetone at ppb levels, with concentrations rising alongside increased lipid metabolism. Our optical sensor offers high accuracy and stability, demonstrating significant potential and value for non-invasive early diabetes diagnosis.

A Doped Surface Ionization Method for Ion Mobility Spectrometry

RATIONALE

Exhaled breath can be used for early warning of disease, with organic nitrogen compounds, including triethylamine (TEA), being linked to various medical conditions. Surface ionization ion mobility spectrometry (SI-IMS) facilitates the direct detection of TEA in exhaled breath. However, the presence of multiple ionization products of TEA poses challenges for both quantitative and qualitative analyses.

METHODS

A doped surface ionization (DSI) method consisting of surface ionization of dopants and gas-phase reaction of samples was proposed, and TEA was detected when combined with an ion mobility spectrometer. TEA at different concentrations and spiked by human breath was detected to evaluate the method's properties.

RESULTS

TEA with concentrations from 5.99 to 30.50 ppb and a relative humidity of 80% was detected. The peak intensity of the protonated TEA ions demonstrated a linear correlation with concentration, yielding a fitted correlation coefficient of R2 = 0.94. A standard deviation less than 0.066% was obtained with 10 replicate analyses of 29.92 ppb TEA, and the recovery rate of the sample was 93.57%.

CONCLUSIONS

The SI-IMS based on the DSI method has the advantages of excellent selective ionization, high accuracy and sensitivity, and remarkable repeatability for detecting TEA. It is a promising method for detecting specific organic nitrogen compounds in exhaled breath.

Recent developments and applications of selected ion flow tube mass spectrometry (SIFT-MS)

Selected ion flow tube mass spectrometry (SIFT-MS) is now recognized as the most versatile analytical technique for the identification and quantification of trace gases down to the parts-per-trillion by volume, pptv, range. This statement is supported by the wide reach of its applications, from real-time analysis, obviating sample collection of very humid exhaled breath, to its adoption in industrial scenarios for air quality monitoring. This review touches on the recent extensions to the underpinning ion chemistry kinetics library and the alternative challenge of using nitrogen carrier gas instead of helium. The addition of reagent anions in the Voice200 series of SIFT-MS instruments has enhanced the analytical capability, thus allowing analyses of volatile trace compounds in humid air that cannot be analyzed using reagent cations alone, as clarified by outlining the anion chemistry involved. Case studies are reviewed of breath analysis and bacterial culture volatile organic compound (VOC), emissions, environmental applications such as air, water, and soil analysis, workplace safety such as transport container fumigants, airborne contamination in semiconductor fabrication, food flavor and spoilage, drugs contamination and VOC emissions from packaging to demonstrate the stated qualities and uniqueness of the new generation SIFT-MS instrumentation. Finally, some advancements that can be made to improve the analytical capability and reach of SIFT-MS are mentioned.

Direct mass spectrometry analysis of exhaled human breath in real-time

The molecular composition of exhaled human breath can reflect various physiological and pathological conditions. Considerable progress has been achieved over the past decade in real-time analysis of exhaled human breath using direct mass spectrometry methods, including selected ion flow tube mass spectrometry, proton transfer reaction mass spectrometry, extractive electrospray ionization mass spectrometry, secondary electrospray ionization mass spectrometry, acetone-assisted negative photoionization mass spectrometry, atmospheric pressure photoionization mass spectrometry, and low-pressure photoionization mass spectrometry. Here, recent developments in direct mass spectrometry analysis of exhaled human breath are reviewed with regard to analytical performance (chemical sensitivity, selectivity, quantitative capabilities) and applications of the developed methods in disease diagnosis, targeted molecular detection, and real-time metabolic monitoring.

Validation of a sensor system for the measurement of breath ammonia using selected-ion flow-tube mass spectrometry

The measurement of trace breath gases is of growing interest for its potential to provide non-invasive physiological information in health and disease. While instrumental techniques such as selected-ion flow-tube mass spectrometry (SIFT-MS) can achieve this, these are less suitable for clinical application. Sensitive sensor-based systems for breath ammonia could be more widely deployed, but have proven challenging to develop. This work demonstrates the sequential analytical validation of an electrochemical impedance-based sensor system for the measurement of ammonia in breath using SIFT-MS. Qualitative and relative responses between the two methods were comparable, although there were consistent differences in absolute concentration. When tested in artificial breath ammonia, sensors had a relative impedance sensitivity of 3.43 × 10-5ppbv-1for each breath in the range of 249-1653 ppbv (r2= 0.87,p< 0.05). When correlated with SIFT-MS using human breath (n= 14), ammonia was detected in the range of 100-700 ppbv (r= 0.78,p< 0.001), demonstrating acceptable sensitivity, reproducibility and dynamic range for clinical application.

Development of probiotic yogurt products incorporated with Lactobacillus kefiranofaciens OSU-BSGOA1 in mono- and coculture with Kluyveromyces marxianus

The bacterium Lactobacillus kefiranofaciens OSU-BDGOA1 and yeast Kluyveromyces marxianus bdgo-ym6 were previously isolated from kefir grains and have shown probiotic traits in mono- and coculture. This research evaluates the effect of introducing probiotic kefir microorganisms in monoculture and in coculture alongside yogurt starter cultures on the physicochemical and rheological properties, volatile flavor compounds, survival of the microorganisms during simulated digestion, and sensory attributes of the final fermented products. The incorporation of L. kefiranofaciens OSU-BDGOA1 in monoculture showed promising outcomes, resulting in a final product showing more solid-like characteristics and potentially improving the texture of the product. There was also a significant increase in the concentration of desirable volatile flavor compounds in the yogurt with the monoculture, particularly 2,3-butanedione, displaying a positive correlation with buttery flavor in the sensory analysis. The inclusion of L. kefiranofaciens in monoculture also promoted better sensory attributes and was significantly better than the yogurt with the coculture with the yeast, showing promising results for the incorporation of this probiotic bacterium into functional fermented dairy products.

Precision detection of select human lung cancer biomarkers and cell lines using honeybee olfactory neural circuitry as a novel gas sensor

Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers at different concentrations and their mixtures at concentration ranges relevant to biomarkers in human breath from parts-per-billion to parts-per-trillion. We also validated this brain-based sensing technology by detecting human non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cell lines using the 'smell' of the cell cultures. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we classified individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create 'synthetic lung cancer' vs. 'synthetic healthy' human breath, honeybee population neuronal responses were able to classify those complex breath mixtures reliably with exceedingly high accuracy (93-100% success rate with a leave-one-trial-out classification method). Finally, we employed this sensor to detect human NSCLC and SCLC cell lines and we demonstrated that honeybee brain olfactory neurons could distinguish between lung cancer vs. healthy cell lines and could differentiate between different NSCLC and SCLC cell lines successfully (82% classification success rate). These results indicate that the honeybee olfactory system can be used as a sensitive biological gas sensor to detect human lung cancer.

The Potential of Fecal Volatile Organic Compound Analysis for the Early Diagnosis of Late-Onset Sepsis in Preterm Infants: A Narrative Review

Early diagnosis and treatment of late-onset sepsis (LOS) is crucial for survival, but challenging. Intestinal microbiota and metabolome alterations precede the clinical onset of LOS, and the preterm gut is considered an important source of bacterial pathogens. Fecal volatile organic compounds (VOCs), formed by physiologic and pathophysiologic metabolic processes in the preterm gut, reflect a complex interplay between the human host, the environment, and microbiota. Disease-associated fecal VOCs can be detected with an array of devices with various potential for the development of a point-of-care test (POCT) for preclinical LOS detection. While characteristic VOCs for common LOS pathogens have been described, their VOC profiles often overlap with other pathogens due to similarities in metabolic pathways, hampering the construction of species-specific profiles. Clinical studies have, however, successfully discriminated LOS patients from healthy individuals using fecal VOC analysis with the highest predictive value for Gram-negative pathogens. This review discusses the current advancements in the development of a non-invasive fecal VOC-based POCT for early diagnosis of LOS, which may potentially provide opportunities for early intervention and targeted treatment and could improve clinical neonatal outcomes. Identification of confounding variables impacting VOC synthesis, selection of an optimal detection device, and development of standardized sampling protocols will allow for the development of a novel POCT in the near future.

Ultratrace eNose Sensing of VOCs toward Breath Analysis Applications Utilizing an eNose-Based Analyzer

This proof-of-principle study presents the ability of the recently developed iLovEnose to measure ultratrace levels of volatile organic compounds (VOCs) in simulated human breath based on the combination of multiple gas sensors. The iLovEnose was developed by our research team as a test bed for gas sensors that can be hosted in three serially connected compact low-volume and temperature-controlled compartments. Herein, the eNose system was equipped with conventional semiconducting metal oxide (MOX) gas sensors using a variety of base technologies providing 11 different sensor signals that were evaluated to determine six VOCs of interest at eight low to ultralow concentration levels (i.e., ranging from 3 to 0.075 ppm) at humid conditions (90% rh at 22 °C). The measurements were randomized and performed four times over a period of 2 weeks. Partial least-squares regression analysis was applied to estimate the concentration of these six analytes. It was shown that the iLovEnose system is able to discriminate between these VOCs and provide reliable quantitative information relevant for future applications in exhaled breath analysis as a diagnostic disease detection or monitoring device.

Volatilome: Smells like microbial spirit

In recent years, the study of volatile compounds has sparked interest due to their implications in signaling and the enormous variety of bioactive properties attributed to them. Despite the absence of analysis methods standardization, there are a multitude of tools and databases that allow the identification and quantification of volatile compounds. These compounds are chemically heterogeneous and their diverse properties are exploited by various fields such as cosmetics, the food industry, agriculture and medicine, some of which will be discussed here. In virtue of volatile compounds being ubiquitous and fast chemical messengers, these molecules mediate a large number of interspecific and intraspecific interactions, which are key at an ecological level to maintaining the balance and correct functioning of ecosystems. This review briefly summarized the role of volatile compounds in inter- and intra-specific relationships as well as industrial applications associated with the use of these compounds that is emerging as a promising field of study.

The Diagnostic Utility of Volatile Organic Compounds in Inflammatory Bowel Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Volatile organic compounds [VOCs] show promise as potential biomarkers of for ulcerative colitis and Crohn's disease, two chronic, idiopathic, gastrointestinal disorders with diagnostic and management challenges. Non-invasive biomarkers aid early diagnosis and management. In this study we review studies of diagnostic accuracy of VOCs in inflammatory bowel disease.

METHODS

A systematic search was carried out on the Pubmed and Scopus databases; with 16 studies reviewed and meta-analysis carried out on 10.

RESULTS

Meta-analysis of 696 inflammatory bowel disease [IBD] cases against 605 controls revealed a pooled sensitivity and specificity of 87% (95% confidence interval [CI], 0.79 - 0.92) and 83% [95% CI, 0.73 - 0.90], respectively. Area under the curve [AUC] was 0.92.

CONCLUSION

VOCs perform very well as non-invasive biomarkers of IBD, with much scope for future improvement and research.

Real-Time Measurement of CH4 in Human Breath Using a Compact CH4/CO2 Sensor

The presence of an elevated amount of methane (CH4) in exhaled breath can be used as a non-invasive tool to monitor certain health conditions. A compact, inexpensive and transportable CH4 sensor is thus very interesting for this purpose. In addition, if the sensor is also able to simultaneously measure carbon dioxide (CO2), one can extract the end-tidal concentration of exhaled CH4. Here, we report on such a sensor based on a commercial detection module using tunable diode laser absorption spectroscopy. It was found that the measured CH4/CO2 values exhibit a strong interference with water vapor. Therefore, correction functions were experimentally identified and validated for both CO2 and CH4. A custom-built breath sampler was developed and tested with the sensor for real-time measurements of CH4 and CO2 in exhaled breath. As a result, the breath sensor demonstrated the capability of accurately measuring the exhaled CH4 and CO2 profiles in real-time. We obtained minimum detection limits of ~80 ppbv for CH4 and ~700 ppmv for CO2 in 1.5 s measurement time.

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.

SARS CoV-2 infection screening via the exhaled breath fingerprint obtained by FTIR spectroscopic gas-phase analysis. A proof of concept

The COVID-19 pandemic remains a global challenge now with the long-COVID arising. Mitigation measures focused on case counting, assessment and determination of variants and their likely targets of infection and transmission, the pursuit of drug treatments, use and enhancement of masks, social distancing, vaccination, post-infection rehabilitation, and mass screening. The latter is of utmost importance given the current scenario of infections, reinfections, and long-term health effects. Research on screening platforms has been developed to provide more sensitive, specific, and reliable tests that are accessible to the entire population and can be used to assess the prognosis of the disease as well as the subsequent health follow-up of patients with sequelae of COVID-19. Therefore, the aim of the present study was the simulation of exhaled breath of COVID-19 patients by evaluation of three identified COVID-19 indicator breath biomarkers (acetone (ACE), acetaldehyde (ACH) and nitric oxide (NO)) by gas-phase infrared spectroscopy as a proof-of-concept principle for the detection of infected patients' exhaled breath fingerprint and subsequent follow-up. The specific fingerprints of each of the compounds and the overall fingerprint were obtained. The synthetic exhaled breath evaluation concept revealed a linearity of r = 0.99 for all compounds, and LODs of 6.42, 13.81, 9.22 ppm, and LOQs of 42.26, 52.57, 69.23 ppm for NO, ACE, and ACH, respectively. This study proves the fundamental feasibility of gas-phase infrared spectroscopy for fingerprinting lung damage biomarkers in exhaled breath of patients with COVID-19. This analysis would allow faster and cheaper screening and follow-up of infected individuals, which could improve mass screening in POC settings.

Novel Models for Accurate Estimation of Air-Blood Partitioning: Applications to Individual Compounds and Complex Mixtures of Neutral Organic Compounds

The air-blood partition coefficient (Kab) is extensively employed in human health risk assessment for chemical exposure. However, current Kab estimation approaches either require an extensive number of parameters or lack precision. In this study, we present two novel and parsimonious models to accurately estimate Kab values for individual neutral organic compounds, as well as their complex mixtures. The first model, termed the GC×GC model, was developed based on the retention times of nonpolar chemical analytes on comprehensive two-dimensional gas chromatography (GC×GC). This model is unique in its ability to estimate the Kab values for complex mixtures of nonpolar organic chemicals. The GC×GC model successfully accounted for the Kab variance (R2 = 0.97) and demonstrated strong prediction power (RMSE = 0.31 log unit) for an independent set of nonpolar chemical analytes. Overall, the GC×GC model can be used to estimate Kab values for complex mixtures of neutral organic compounds. The second model, termed the partition model (PM), is based on two types of partition coefficients: octanol to water (Kow) and air to water (Kaw). The PM was able to effectively account for the variability in Kab data (n = 344), yielding an R2 value of 0.93 and root-mean-square error (RMSE) of 0.34 log unit. The predictive power and explanatory performance of the PM were found to be comparable to those of the parameter-intensive Abraham solvation models (ASMs). Additionally, the PM can be integrated into the software EPI Suite, which is widely used in chemical risk assessment for initial screening. The PM provides quick and reliable estimation of Kab compared to ASMs, while the GC×GC model is uniquely suited for estimating Kab values for complex mixtures of neutral organic compounds. In summary, our study introduces two novel and parsimonious models for the accurate estimation of Kab values for both individual compounds and complex mixtures.

Increasing the Robustness of SIFT-MS Volatilome Fingerprinting by Introducing Notional Analyte Concentrations

Selected ion flow tube-mass spectrometry (SIFT-MS) is an analytical technique for volatile detection and quantification. SIFT-MS can be applied in a "white box" approach, measuring concentrations of target compounds, or as a "black box" fingerprinting technique, scanning all product ions during a full scan. Combining SIFT-MS full scan data acquired from multibatches or large-scale experiments remains problematic due to signal fluctuation over time. The standard approach of normalizing full scan data to the total signal intensity was insufficient. This study proposes a new approach to correct SIFT-MS fingerprinting data. In this concept, all of the product ions from a full scan are considered individual compounds for which notional concentrations can be calculated. Converting ion count rates into notional analyte concentrations accounts for any changes in the instrument parameters. The benefits of the proposed approach are demonstrated on three years of data from both multibatches and long-term experiments showing a significant reduction of system-induced fluctuations providing a better focus on the changes of interest.

Prediction of systemic free and total valproic acid by off-line analysis of exhaled breath in epileptic children and adolescents

Therapeutic drug monitoring (TDM) of medications with a narrow therapeutic window is a common clinical practice to minimize toxic effects and maximize clinical outcomes. Routine analyses rely on the quantification of systemic blood concentrations of drugs. Alternative matrices such as exhaled breath are appealing because of their inherent non-invasive nature. This is especially the case for pediatric patients. We have recently showcased the possibility of predicting systemic concentrations of valproic acid (VPA), an anti-seizure medication by real-time breath analysis in two real clinical settings. This approach, however, comes with the limitation of the patients having to physically exhale into the mass spectrometer. This restricts the possibility of sampling from patients not capable or available to exhale into the mass spectrometer located on the hospital premises. In this work, we developed an alternative method to overcome this limitation by collecting the breath samples in customized bags and subsequently analyzing them by secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). A total ofn= 40 patients (mean ± SD, 11.5 ± 3.5 y.o.) diagnosed with epilepsy and taking VPA were included in this study. The patients underwent three measurements: (i) serum concentrations of total and free VPA, (ii) real-time breath analysis and (iii) off-line analysis of exhaled breath collected in bags. The agreement between the real-time and the off-line breath analysis methods was evaluated using Lin's concordance correlation coefficient (CCC). CCC was computed for ten mass spectral predictors of VPA concentrations. Lin's CCC was >0.6 for all VPA-associated features, except for two low-signal intensity isotopic peaks. Finally, free and total serum VPA concentrations were predicted by cross validating the off-line data set. Support vector machine algorithms provided the most accurate predictions with a root mean square error of cross validation of 29.0 ± 7.4 mg l-1and 3.9 ± 1.4 mg l-1for total and free VPA (mean ± SD), respectively. As a secondary analysis, we explored whether exhaled metabolites previously associated with side-effects and response to medication could be rendered by the off-line analysis method. We found that five features associated with side effects showed a CCC > 0.6, whereas none of the drug response-associated peaks reached this cut-off. We conclude that the clinically relevant free fraction of VPA can be predicted by this combination of off-line breath collection with rapid SESI-HRMS analysis. This opens new possibilities for breath based TDM in clinical settings.

How to Use Ion-Molecule Reaction Data Previously Obtained in Helium at 300 K in the New Generation of Selected Ion Flow Tube Mass Spectrometry Instruments Operating in Nitrogen at 393 K

Selected ion flow tube mass spectrometry (SIFT-MS) instruments have significantly developed since this technique was introduced more than 20 years ago. Most studies of the ion-molecule reaction kinetics that are essential for accurate analyses of trace gases and vapors in air and breath were conducted in He carrier gas at 300 K, while the new SIFT-MS instruments (optimized to quantify concentrations down to parts per trillion by volume) operate with N₂ carrier gas at 393 K. Thus, we pose the question of how to reuse the data from the extensive body of previous literature using He at room temperature in the new instruments operating with N₂ carrier gas at elevated temperatures. Experimentally, we found the product ions to be qualitatively similar, although there were differences in the branching ratios, and some reaction rate coefficients were lower in the heated N₂ carrier gas. The differences in the reaction kinetics may be attributed to temperature, an electric field in the current flow tubes, and the change from He to N₂ carrier gas. These results highlight the importance of adopting an updated reaction kinetics library that accounts for the new instruments' specific conditions. In conclusion, almost all previous rate coefficients may be used after adjustment for higher temperatures, while some product ion branching ratios need to be updated.

Evaluation of Linkers' Influence on Peptide-Based Piezoelectric Biosensors' Sensitivity to Aldehydes in the Gas Phase

Recent findings qualified aldehydes as potential biomarkers for disease diagnosis. One of the possibilities is to use electrochemical biosensors in point-of-care (PoC), but these need further development to overcome some limitations. Currently, the primary goal is to enhance their metrological parameters in terms of sensitivity and selectivity. Previous findings indicate that peptide OBPP4 (KLLFDSLTDLKKKMSEC-NH₂) is a promising candidate for further development of aldehyde-sensitive biosensors. To increase the affinity of a receptor layer to long-chain aldehydes, a structure stabilization of the peptide active site via the incorporation of different linkers was studied. Indeed, the incorporation of linkers improved sensitivity to and binding of aldehydes in comparison to that of the original peptide-based biosensor. The tendency to adopt disordered structures was diminished owing to the implementation of suitable linkers. Therefore, to improve the metrological characteristics of peptide-based piezoelectric biosensors, linkers were added at the C-terminus of OBPP4 peptide (KLLFDSLTDLKKKMSE-linker-C-NH₂). Those linkers consist of proteinogenic amino acids from group one: glycine, L-proline, L-serine, and non proteinogenic amino acids from group two: β-alanine, 4-aminobutyric acid, and 6-aminohexanoic acid. Linkers were evaluated with in silico studies, followed by experimental verification. All studied linkers enhanced the detection of aldehydes in the gas phase. The highest difference in frequency (60 Hz, nonanal) was observed between original peptide-based biosensors and ones based on peptides modified with the GSGSGS linker. It allowed evaluation of the limit of detection for nonanal at the level of 2 ppm, which is nine times lower than that of the original peptide. The highest sensitivity values were also obtained for the GSGSGS linker: 0.3312, 0.4281, and 0.4676 Hz/ppm for pentanal, octanal, and nonanal, respectively. An order of magnitude increase in sensitivity was observed for the six linkers used. Generally, the linker's rigidity and the number of amino acid residues are much more essential for biosensors' metrological characteristics than the amino acid sequence itself. It was found that the longer the linkers, the better the effect on docking efficiency.

Exhaled Biomarkers for Point-of-Care Diagnosis: Recent Advances and New Challenges in Breathomics

Cancers, chronic diseases and respiratory infections are major causes of mortality and present diagnostic and therapeutic challenges for health care. There is an unmet medical need for non-invasive, easy-to-use biomarkers for the early diagnosis, phenotyping, predicting and monitoring of the therapeutic responses of these disorders. Exhaled breath sampling is an attractive choice that has gained attention in recent years. Exhaled nitric oxide measurement used as a predictive biomarker of the response to anti-eosinophil therapy in severe asthma has paved the way for other exhaled breath biomarkers. Advances in laser and nanosensor technologies and spectrometry together with widespread use of algorithms and artificial intelligence have facilitated research on volatile organic compounds and artificial olfaction systems to develop new exhaled biomarkers. We aim to provide an overview of the recent advances in and challenges of exhaled biomarker measurements with an emphasis on the applicability of their measurement as a non-invasive, point-of-care diagnostic and monitoring tool.

Harnessing insect olfactory neural circuits for detecting and discriminating human cancers

There is overwhelming evidence that presence of cancer alters cellular metabolic processes, and these changes are manifested in emitted volatile organic compound (VOC) compositions of cancer cells. Here, we take a novel forward engineering approach by developing an insect olfactory neural circuit-based VOC sensor for cancer detection. We obtained oral cancer cell culture VOC-evoked extracellular neural responses from in vivo insect (locust) antennal lobe neurons. We employed biological neural computations of the antennal lobe circuitry for generating spatiotemporal neuronal response templates corresponding to each cell culture VOC mixture, and employed these neuronal templates to distinguish oral cancer cell lines (SAS, Ca9-22, and HSC-3) vs. a non-cancer cell line (HaCaT). Our results demonstrate that three different human oral cancers can be robustly distinguished from each other and from a non-cancer oral cell line. By using high-dimensional population neuronal response analysis and leave-one-trial-out methodology, our approach yielded high classification success for each cell line tested. Our analyses achieved 76-100% success in identifying cell lines by using the population neural response (n = 194) collected for the entire duration of the cell culture study. We also demonstrate this cancer detection technique can distinguish between different types of oral cancers and non-cancer at different time-matched points of growth. This brain-based cancer detection approach is fast as it can differentiate between VOC mixtures within 250 ms of stimulus onset. Our brain-based cancer detection system comprises a novel VOC sensing methodology that incorporates entire biological chemosensory arrays, biological signal transduction, and neuronal computations in a form of a forward-engineered technology for cancer VOC detection.

Diagnosis by Volatile Organic Compounds in Exhaled Breath in Exhaled Breath from Patients with Gastric and Colorectal Cancers

One in three cancer deaths worldwide are caused by gastric and colorectal cancer malignancies. Although the incidence and fatality rates differ significantly from country to country, the rates of these cancers in East Asian nations such as South Korea and Japan have been increasing each year. Above all, the biggest danger of this disease is how challenging it is to recognize in its early stages. Moreover, most patients with these cancers do not present with any disease symptoms before receiving a definitive diagnosis. Currently, volatile organic compounds (VOCs) are being used for the early prediction of several other diseases, and research has been carried out on these applications. Exhaled VOCs from patients possess remarkable potential as novel biomarkers, and their analysis could be transformative in the prevention and early diagnosis of colon and stomach cancers. VOCs have been spotlighted in recent studies due to their ease of use. Diagnosis on the basis of patient VOC analysis takes less time than methods using gas chromatography, and results in the literature demonstrate that it is possible to determine whether a patient has certain diseases by using organic compounds in their breath as indicators. This study describes how VOCs can be used to precisely detect cancers; as more data are accumulated, the accuracy of this method will increase, and it can be applied in more fields.

Kinetics of reactions of NH4 + with some biogenic organic molecules and monoterpenes in helium and nitrogen carrier gases: A potential reagent ion for selected ion flow tube mass spectrometry

RATIONALE

To assess the suitability of NH₄ ⁺ as a reagent ion for trace gas analysis by selected ion flow tube mass spectrometry, SIFT-MS, its ion chemistry must be understood. Thus, rate coefficients and product ions for its reactions with typical biogenic molecules and monoterpenes need to be experimentally determined in both helium, He, and nitrogen, N₂ , carrier gases.

METHODS

NH₄ ⁺ and H₃ O⁺ were generated in a microwave gas discharge through an NH₃ and H₂ O vapour mixture and, after m/z selection, injected into He and N₂ carrier gas. Using the conventional SIFT method, NH₄ ⁺ reactions were then studied with M, the biogenic molecules acetone, 1-propanol, 2-butenal, trans-2-heptenal, heptanal, 2-heptanone, 2,3-heptanedione and 15 monoterpene isomers to obtain rate coefficients, k, and product ion branching ratios. Polarisabilities and dipole moments of the reactant molecules and the enthalpy changes in proton transfer reactions were calculated using density functional theory.

RESULTS

The k values for the reactions of the biogenic molecules were invariably faster in N₂ than in He but similar in both bath gases for the monoterpenes. Adducts NH₄ ⁺ M were the dominant product ions in He and N₂ for the biogenic molecules, whereas both MH⁺ and NH₄ ⁺ M product ions were observed in the monoterpene reactions; the monoterpene ratio correlating (R²  = 0.7) with the proton affinity, PA, of the monoterpene molecule as calculated. The data indicate that this adduct ion formation is the result of bimolecular rather than termolecular association.

CONCLUSIONS

NH₄ ⁺ can be a useful reagent ion for SIFT-MS analyses of molecules with PA(M) < PA(NH₃ ) when the dominant single product ion is the adduct NH₄ ⁺ M. For molecules with PA(M) > PA(NH₃ ), such as monoterpenes, both MH⁺ and NH₄ ⁺ M ions are likely products, which must be determined along with k by experiment.

Volatolomic urinary profile analysis for diagnosis of the early stage of lung cancer

Nowadays in clinical practice there is a pressing need for potential biomarkers that can identify lung cancer at early stage before becoming symptomatic or detectable by conventional means. Several researchers have independently pointed out that the volatile organic compounds (VOCs) profile can be considered as a lung cancer fingerprint useful for diagnosis. In particular, 16% of volatiles contributing to the human volatilome are found in urine, which is therefore an ideal sample medium. Its analysis through non-invasive, relatively low-cost and straightforward techniques could offer great potential for the early diagnosis of lung cancer. In this study, urinary VOCs were analysed with a gas chromatography-ion mobility spectrometer (GC-IMS) and an electronic nose (e-nose) made by a matrix of twelve quartz microbalances (QMBs) complemented by a photoionization detector (PID). This clinical prospective study involved 127 individuals, divided into two groups: 46 with lung cancer stage I-II-III confirmed by computerized tomography (CT) or positron emission tomography-(PET) imaging techniques and histology (biopsy), and 81 healthy controls. Both instruments provided a multivariate signal which, after being analysed by a machine learning algorithm, identified eight VOCs that could distinguish lung cancer patients from healthy ones. The eight VOCs are 2-pentanone, 2-hexenal, 2-hexen-1-ol, hept-4-en-2-ol, 2-heptanone, 3-octen-2-one, 4-methylpentanol, 4-methyl-octane. Results show that GC-IMS identifies lung cancer with respect to the control group with a diagnostic accuracy of 88%. Sensitivity resulted as being 85%, and specificity was 90% - Area Under the Receiver Operating Characteristics (AUROC): 0.91. The contribution made by the e-nose was also important, even though the results were slightly less sensitive with an accuracy of 71.6%. Moreover, of the eight VOCs identified as potential biomarkers, five VOCs had a high sensitivity (p≤ 0.06) for early stage (stage I) lung cancer.

Changes in the urine volatile metabolome throughout growth of transplanted hepatocarcinoma

Trained detection dogs distinguish between urine samples from healthy organisms and organisms with malignant tumors, suggesting that the volatile urine metabolome contains information about tumor progression. The aim of this study was to determine whether the stage of tumor growth affects the chemical differences in the urine of mice and to what extent the "olfactory image of disease" perceived by dogs coincides with the "image of disease" recorded by the mass spectrometer. We used a novel laser ionization mass spectrometry method and propose a mass spectrometric analysis without detailed interpretation of the spectrum of volatile metabolomes in urine. The mass spectrometer we use works without sample preparation and registers volatile organic compounds in air at room temperature without changing the pH of the sample, i.e. under conditions similar to those in which dogs solve the same problem. The experimental cancer models were male BDF-f1 hybrid mice transplanted with hepatocarcinoma tissue, and similar mice transplanted with healthy liver tissue were used as controls. Our data show that both dogs and our proposed laser mass spectrometry method are able to detect both the entire spectrum of volatile organic compounds associated with the disease and minor changes in this spectrum during its course.

Ternary association reactions of H3 O+ , NO+ and O2 +• with N2 , O2 , CO2 and H2 O; implications for selected ion flow tube mass spectrometry analyses of air and breath

RATIONALE

The reactions of the reagent ions used for trace gas analysis in selected ion flow tube mass spectrometry (SIFT-MS), R⁺ , viz. H₃ O⁺ , NO⁺ and O₂ ⁺ , with the major gases in air and breath samples, M, viz. N₂ , O₂ , CO₂ and H₂ O, are investigated. These reactions are seen to form weakly-bound adduct ions, R⁺ M, by ternary association reactions that must not be mistaken for genuine volatile organic compound (VOC) analyte ions.

METHODS

The ternary association rate coefficients mediated by helium (He) carrier gas atoms, k_3a , have been determined for all combinations of R⁺ and M, which form R⁺ M adduct ions ranging in m/z from 47 (H₃ O⁺ N₂ ) to 76 (O₂ ^+• CO₂ ). This was achieved by adding variable amounts of M (up to 0.5 mbar pressure) into the He carrier gas (pressure of 1.33 mbar) in a SIFT-MS flow tube at 300 K. Parabolic curvature was observed on some of the semi-logarithmic decay curves that allowed the rate coefficients mediated by M molecules, k_3b , to be estimated.

RESULTS

Values of k_3a were found to range from 1 × 10^-31  cm⁶  s^-1 to 5 × 10^-29  cm⁶  s^-1 , which form mass spectral R⁺ M "ghost peaks" of significant strength when analysing VOCs at parts-per-billion concentrations. It was seen that the R⁺ M adduct ions (except when M is H₂ O) react with H₂ O molecules by ligand switching forming the readily recognised monohydrates of the initial reagent cations R⁺ H₂ O. Whilst this ligand switching diminishes the R⁺ M adduct ghost peaks, it does not eliminate them entirely.

CONCLUSIONS

The significance of these adduct ions for trace gas analysis by SIFT-MS in the low m/z region is alluded to, and some examples are given of m/z spectral overlaps of the R⁺ M and R⁺ H₂ O adduct cations with analyte cations of VOCs formed by analysis of complex media like exhaled breath, warning that ghost peaks will be enhanced using nitrogen carrier gas in SIFT-MS.

Sensitivity of secondary electrospray ionization mass spectrometry to a range of volatile organic compounds: Ligand switching ion chemistry and the influence of Zspray™ guiding electric fields

RATIONALE

Secondary electrospray ionization (SESI) is currently only semi-quantitative. In the Zspray™ arrangement of SESI-MS, the transfer of ions from near atmospheric pressure to a triple quadrupole is achieved by guiding electric fields that partially desolvate both reagent and analyte ions which must be understood. Also, to make SESI-MS more quantitative, the mechanisms and the kinetics of the reaction processes, especially ligand switching reactions of hydrated hydronium reagent ions, H₃ O⁺ (H₂ O)_n , with volatile organic compound (VOC) molecules, need to be understood.

METHODS

A modified Zspray™ ESI ion source operating at sub-atmospheric pressure with analyte sample gas introduced via an inlet coaxial with the spray was used. Variation of the ion-guiding electric fields was used to reveal the degree of desolvation of both reagent and analyte ions. The instrument sensitivity was determined for several classes of VOCs by introducing bag samples of suitably varying concentrations as quantified on-line using selected ion flow tube MS.

RESULTS

Electric field desolvation resulted in largely protonated VOCs, MH⁺ , and their monohydrates, MH⁺ H₂ O, and for some VOCs proton-bound dimer ions, MH⁺ M, were formed. There was a highly linear response of the ion signal to the measured VOC sample concentration, which provided the instrument sensitivities, S, for 25 VOCs. The startling results show very wide variations in S from near 0 to 1 for hydrocarbons, and up to 100, on a relative scale, for polar compounds such as monoketones and unsaturated aldehydes.

CONCLUSIONS

The complex ion chemistry occurring in the SESI ion source, largely involving gas-phase ligand switching, results in widely variable sensitivities for different classes of VOCs. The sensitivity is observed to depend on the dipole moment and proton affinity of the analyte VOC molecule, M, and to decrease with the observed fraction of MH⁺ H₂ O, but other yet unrecognized factors must play a significant role.

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.

Selected ion flow tube mass spectrometry for targeted analysis of volatile organic compounds in human breath

The analysis of volatile organic compounds (VOCs) within breath for noninvasive disease detection and monitoring is an emergent research field that has the potential to reshape current clinical practice. However, adoption of breath testing has been limited by a lack of standardization. This protocol provides a comprehensive workflow for online and offline breath analysis using selected ion flow tube mass spectrometry (SIFT-MS). Following the suggested protocol, 50 human breath samples can be analyzed and interpreted in <3 h. Key advantages of SIFT-MS are exploited, including the acquisition of real-time results and direct compound quantification without need for calibration curves. The protocol includes details of methods developed for targeted analysis of disease-specific VOCs, specifically short-chain fatty acids, aldehydes, phenols, alcohols and alkanes. A procedure to make custom breath collection bags is also described. This standardized protocol for VOC analysis using SIFT-MS is intended to provide a basis for wider application and the use of breath analysis in clinical studies.

Reagent and analyte ion hydrates in secondary electrospray ionization mass spectrometry (SESI-MS), their equilibrium distributions and dehydration in an ion transfer capillary: Modelling and experiments

RATIONALE

Secondary electrospray ionization (SESI) in a water spray environment at atmospheric pressure involves the reactions of hydrated hydronium reagent ions, H₃ O⁺ (H₂ O)_n , with trace analyte compounds in air samples. Understanding the formation and dehydration of reagent and analyte ions is the foundation for meaningful quantification of trace compounds by SESI-mass spectrometry (MS).

METHODS

A numerical model based on gas-phase ion thermochemistry is developed that describes equilibria in H₃ O⁺ (H₂ O)_n reagent cluster ion distributions and ligand switching reactions with polar NH₃ molecules leading to equilibrated hydrated ammonium ions NH₄ ⁺ (H₂ O)_m . The model predictions are compared with experimental results obtained using a cylindrical SESI source coupled to an ion-trap mass spectrometer via a heated ion transfer capillary. Non-polar isoprene, C₅ H₈ , was used to further probe the nature of the reagent ions.

RESULTS

Equilibrium distributions of H₃ O⁺ (H₂ O)_n ions and their reactions with NH₃ molecules have been characterized by the model in the near-atmospheric pressure SESI source. NH₃ analyte molecules displace H₂ O ligands from the H₃ O⁺ (H₂ O)_n ions at the collisional rate forming NH₄ ⁺ (H₂ O)_m ions, which travel through the heated ion transfer capillary losing H₂ O molecules. The data for variable NH₃ concentrations match the model predictions and the C₅ H₈ test substantiates the notion of dehydration in the heated capillary.

CONCLUSIONS

Large cluster ions formed in the SESI region are dehydrated to H₃ O⁺ (H₂ O)_1,2,3 and NH₄ ⁺ (H₂ O)_1,2 while passing through the heated capillary, and considerable diffusion losses also occur. This phenomenon is also predicted for other polar analyte molecules, A, that can undergo similar switching reactions, thus forming AH⁺ and AH⁺ (H₂ O)_m analyte ions.

Breathomics: Review of Sample Collection and Analysis, Data Modeling and Clinical Applications

Metabolomics research is rapidly gaining momentum in disease diagnosis, on top of other Omics technologies. Breathomics, as a branch of metabolomics is developing in various frontiers, for early and noninvasive monitoring of disease. This review starts with a brief introduction to metabolomics and breathomics. A number of important technical issues in exhaled breath collection and factors affecting the sampling procedures are presented. We review the recent progress in metabolomics approaches and a summary of their applications on the respiratory and non-respiratory diseases investigated by breath analysis. Recent reports on breathomics studies retrieved from Scopus and Pubmed were reviewed in this work. We conclude that analyzing breath metabolites (both volatile and nonvolatile) is valuable in disease diagnoses, and therefore believe that breathomics will turn into a promising noninvasive discipline in biomarker discovery and early disease detection in personalized medicine. The problem of wide variations in the reported metabolite concentrations from breathomics studies should be tackled by developing more accurate analytical methods and sophisticated numerical analytical alogorithms.

Noninvasive monitoring of fibre fermentation in healthy volunteers by analyzing breath volatile metabolites: lessons from the FiberTAG intervention study

The fermentation of dietary fibre (DF) leads to the production of bioactive metabolites, the most volatile ones being excreted in the breath. The aim of this study was to analyze the profile of exhaled breath volatile metabolites (BVM) and gastrointestinal symptoms in healthy volunteers after a single ingestion of maltodextrin (placebo) versus chitin-glucan (CG), an insoluble DF previously shown to be fermented into short-chain fatty acids (SCFA) by the human microbiota in vitro. Maltodextrin (4.5 g at day 0) or CG (4.5 g at day 2) were added to a standardized breakfast in fasting healthy volunteers (n = 15). BVM were measured using selected ion flow tube mass spectrometry (SIFT-MS) throughout the day. A single ingestion of 4.5 g CG did not induce significant gastrointestinal discomfort. Untargeted metabolomics analysis of breath highlighted that 13 MS-fragments (among 408 obtained from ionizations of breath) discriminated CG versus maltodextrin acute intake in the posprandial state. The targeted analysis revealed that CG increased exhaled butyrate and 5 other BVM - including the microbial metabolites 2,3-butanedione and 3-hydroxybutanone - with a peak observed 6 h after CG intake. Correlation analyses with fecal microbiota (Illumina 16S rRNA sequencing) spotlighted Mitsuokella as a potential genus responsible for the presence of butyric acid, triethylamine and 3-hydroxybutanone in the breath. In conclusion, measuring BMV in the breath reveals the microbial signature of the fermentation of DF after a single ingestion. This protocol allows to analyze the time-course of released bioactive metabolites that could be proposed as new biomarkers of DF fermentation, potentially linked to their biological properties. Trial registration: Clinical Trials NCT03494491. Registered 11 April 2018 - Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03494491.

Analysis of urinary VOCs using mass spectrometric methods to diagnose cancer: A review

The development of non-invasive screening techniques for early cancer detection is one of the greatest scientific challenges of the 21st century. One promising emerging method is the analysis of volatile organic compounds (VOCs). VOCs are low molecular weight substances generated as final products of cellular metabolism and emitted through a variety of biological matrices, such as breath, blood, saliva and urine. Urine stands out for its non-invasive nature, availability in large volumes, and the high concentration of VOCs in the kidneys. This review provides an overview of the available data on urinary VOCs that have been investigated in cancer-focused clinical studies using mass spectrometric (MS) techniques. A literature search was conducted in ScienceDirect, Pubmed and Web of Science, using the keywords "Urinary VOCs", "VOCs biomarkers" and "Volatile cancer biomarkers" in combination with the term "Mass spectrometry". Only studies in English published between January 2011 and May 2020 were selected. The three most evaluated types of cancers in the reviewed studies were lung, breast and prostate, and the most frequently identified urinary VOC biomarkers were hexanal, dimethyl disulfide and phenol; with the latter seeming to be closely related to breast cancer. Additionally, the challenges of analyzing urinary VOCs using MS-based techniques and translation to clinical utility are discussed. The outcome of this review may provide valuable information to future studies regarding cancer urinary VOCs.

Understanding Gas Phase Ion Chemistry Is the Key to Reliable Selected Ion Flow Tube-Mass Spectrometry Analyses

Ion-molecule reactions (IMR) are at the very core of trace gas analyses in modern chemical ionization (CI) mass spectrometer instruments, which are increasingly being used in diverse areas of research and industry. The focus of this Perspective is on the ion chemistry that underpins gas-phase analytical CI methods. Special attention is given to the soft chemical ionization method known as selected ion flow tube-mass spectrometry (SIFT-MS). The processes involved in the ion chemistry of the reagent cations, H₃O⁺, NO⁺, and O₂^+•, and the anions, O^-•, O₂^-•, OH^-, and NO₂^-, are discussed in some detail. Stressed throughout is that an understanding of these processes is mandatory to obtain reliable analyses of humid gaseous media such as ambient air and exhaled breath. It is indicated that further research is needed to understand the consequences of replacing helium in some situations by the more readily available nitrogen as the carrier gas in SIFT-MS.

Real-time selected ion flow tube mass spectrometry to assess short- and long-term variability in oral and nasal breath

Breath-based non-invasive diagnostics have the potential to provide valuable information about a person's health status. However, they are not yet widely used in clinical practice due to multiple factors causing variability and the lack of standardized procedures. This study focuses on the comparison of oral and nasal breathing, and on the variability of volatile metabolites over the short and long term. Selected ion flow tube mass spectrometry (SIFT-MS) was used for online analysis of selected volatile metabolites in oral and nasal breath of 10 healthy individuals five times in one day (short-term) and six times spread over three weeks (long-term), resulting in nearly 100 breath samplings. Intra-class correlation coefficients (ICCs) were used to assess short- and long-term biological variability. Additionally, the composition of ambient air was analyzed at different samplings. The selected volatiles common in exhaled breath were propanol, 2,3-butanedione, acetaldehyde, acetone, ammonia, dimethyl sulfide, isoprene, pentane, and propanal. Additionally, environmental compounds benzene and styrene were analyzed as well. Volatile metabolite concentrations in ambient air were not correlated with those in exhaled breath and were significantly lower than in breath samples. All volatiles showed significant correlation between oral and nasal breath. Five were significantly higher in oral breath compared to nasal breath, while for acetone, propanal, dimethyl sulfide, and ammonia, concentrations were similar in both matrices. Variability depended on the volatile metabolite. Most physiologically relevant volatiles (acetone, isoprene, propanol, acetaldehyde) showed good to very good biological reproducibility (ICC > 0.61) mainly in oral breath and over a short-term period of one day. Both breathing routes showed relatively similar patterns; however, bigger differences were expected. Therefore, since sampling from the mouth is practically more easy, the latter might be preferred.