Exploring the ageing methylome in the model insect, Nasonia vitripennis.

BACKGROUND: The ageing process is a multifaceted phenomenon marked by the gradual deterioration of cellular and organismal functions, accompanied by an elevated susceptibility to diseases. The intricate interplay between genetic and environmental factors complicates research, particularly in complex mammalian models. In this context, simple invertebrate organisms have been pivotal, but the current models lack detectable DNA methylation limiting the exploration of this critical epigenetic ageing mechanism. This study introduces Nasonia vitripennis, the jewel wasp, as an innovative invertebrate model for investigating the epigenetics of ageing. Leveraging its advantages as a model organism and possessing a functional DNA methylation system, Nasonia emerges as a valuable addition to ageing research. RESULTS: Whole-genome bisulfite sequencing unveiled dynamic alterations in DNA methylation, with differentially methylated CpGs between distinct time points in both male and female wasps. These changes were associated with numerous genes, enriching for functions related to telomere maintenance, histone methylation, and mRNA catabolic processes. Additionally, other CpGs were found to be variably methylated at each timepoint. Sex-specific effects on epigenetic entropy were observed, indicating differential patterns in the loss of epigenetic stability over time. Constructing an epigenetic clock containing 19 CpGs revealed a robust correlation between epigenetic age and chronological age. CONCLUSIONS: Nasonia vitripennis emerges as a promising model for investigating the epigenetics of ageing, shedding light on the intricate dynamics of DNA methylation and their implications for age-related processes. This research not only expands the repertoire of ageing models but also opens avenues for deeper exploration of epigenetic mechanisms in the context of ageing.

Breath testing for SARS-CoV-2 infection.

BACKGROUND: From a public health perspective, the identification of individuals with mild respiratory symptoms due to SARS-CoV-2 infection is important to contain the spread of the disease. The objective of this study was to identify volatile organic compounds (VOCs) in exhaled breath common to infection with different variants of the SARS-CoV-2 virus to inform the development of a point-of-care breath test to detect infected individuals with mild symptoms. METHODS: A prospective, real-world, observational study was conducted on mildly symptomatic out-patients presenting to community test-sites for RT-qPCR SARS-CoV-2 testing when the Alpha, Beta, and Delta variants were driving the COVID-19 pandemic. VOCs in exhaled breath were compared between PCR-positive and negative individuals using TD-GC-ToF-MS. Candidate VOCs were tested in an independent set of samples collected during the Omicron phase of the pandemic. FINDINGS: Fifty breath samples from symptomatic RT-qPCR positive and 58 breath samples from test-negative, but symptomatic participants were compared. Of the 50 RT-qPCR-positive participants, 22 had breath sampling repeated 8-12 weeks later. PCA-X model yielded 12 distinct VOCs that discriminated SARS-CoV-2 active infection compared to recovery/convalescence period, with an area under the receiver operator characteristic curve (AUROC), of 0.862 (0.747-0.977), sensitivity, and specificity of 82% and 86%, respectively. PCA-X model from 50 RT-qPCR positive and 58 negative symptomatic participants, yielded 11 VOCs, with AUROC of 0.72 (0.604-0.803) and sensitivity of 72%, specificity 65.5%. The 11 VOCs were validated in a separate group of SARS-CoV-2 Omicron positive patients' vs healthy controls demonstrating an AUROC of 0.96 (95% CI 0.827-0.993) with sensitivity of 80% specificity of 90%. INTERPRETATION: Exhaled breath analysis is a promising non-invasive, point-of-care method to detect mild COVID-19 infection. FUNDING: Funding for this study was a competitive grant awarded from the Vancouver Coastal Research Institute as well as funding from the BC Cancer Foundation.

Peppermint protocol: first results for gas chromatography-ion mobility spectrometry.

ThePeppermint Initiativeseeks to inform the standardisation of breath analysis methods. FivePeppermint Experimentswith gas chromatography-ion mobility spectrometry (GC-IMS), operating in the positive mode with a tritium3H 5.68 keV, 370 MBq ionisation source, were undertaken to provide benchmarkPeppermint Washoutdata for this technique, to support its use in breath-testing, analysis, and research. Headspace analysis of a peppermint-oil capsule by GC-IMS with on-column injection (0.5 cm3) identified 12 IMS responsive compounds, of which the four most abundant were: eucalyptol;ß-pinene;α-pinene; and limonene. Elevated concentrations of these four compounds were identified in exhaled-breath following ingestion of a peppermint-oil capsule. An unidentified compound attributed as a volatile catabolite of peppermint-oil was also observed. The most intense exhaled peppermint-oil component was eucalyptol, which was selected as a peppermint marker for benchmarking GC-IMS. Twenty-five washout experiments monitored levels of exhaled eucalyptol, by GC-IMS with on-column injection (0.5 cm3), att= 0 min, and then att+ 60,t+ 90,t+ 165,t+ 285 andt+ 360 min from ingestion of a peppermint capsule resulting in 148 peppermint breath analyses. Additionally, thePeppermint Washoutdata was used to evaluate clinical deployments with a further five washout tests run in clinical settings generating an additional 35 breath samples. Regression analysis yielded an average extrapolated time taken for exhaled eucalyptol levels to return to baseline values to be 429 ± 62 min (±95% confidence-interval). The benchmark value was assigned to the lower 95% confidence-interval, 367 min. Further evaluation of the data indicated that the maximum number of volatile organic compounds discernible from a 0.5 cm3breath sample was 69, while the use of an in-line biofilter appeared to reduce this to 34.

Pirfenidone Has Anti-fibrotic Effects in a Tissue-Engineered Model of Human Cardiac Fibrosis.

A fundamental process in the development and progression of heart failure is fibrotic remodeling, characterized by excessive deposition of extracellular matrix proteins in response to injury. Currently, therapies that effectively target and reverse cardiac fibrosis are lacking, warranting novel therapeutic strategies and reliable methods to study their effect. Using a gelatin methacryloyl hydrogel, human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) and human fetal cardiac fibroblasts (hfCF), we developed a multi-cellular mechanically tunable 3D in vitro model of human cardiac fibrosis. This model was used to evaluate the effects of a promising anti-fibrotic drug-pirfenidone-and yields proof-of-concept of the drug testing potential of this platform. Our study demonstrates that pirfenidone has anti-fibrotic effects but does not reverse all TGF-ß1 induced pro-fibrotic changes, which provides new insights into its mechanism of action.

Fast and automated biomarker detection in breath samples with machine learning.

Volatile organic compounds (VOCs) in human breath can reveal a large spectrum of health conditions and can be used for fast, accurate and non-invasive diagnostics. Gas chromatography-mass spectrometry (GC-MS) is used to measure VOCs, but its application is limited by expert-driven data analysis that is time-consuming, subjective and may introduce errors. We propose a machine learning-based system to perform GC-MS data analysis that exploits deep learning pattern recognition ability to learn and automatically detect VOCs directly from raw data, thus bypassing expert-led processing. We evaluate this new approach on clinical samples and with four types of convolutional neural networks (CNNs): VGG16, VGG-like, densely connected and residual CNNs. The proposed machine learning methods showed to outperform the expert-led analysis by detecting a significantly higher number of VOCs in just a fraction of time while maintaining high specificity. These results suggest that the proposed novel approach can help the large-scale deployment of breath-based diagnosis by reducing time and cost, and increasing accuracy and consistency.

The Impact of a Graded Maximal Exercise Protocol on Exhaled Volatile Organic Compounds: A Pilot Study.

Exhaled volatile organic compounds (VOCs) are of interest due to their minimally invasive sampling procedure. Previous studies have investigated the impact of exercise, with evidence suggesting that breath VOCs reflect exercise-induced metabolic activity. However, these studies have yet to investigate the impact of maximal exercise to exhaustion on breath VOCs, which was the main aim of this study. Two-litre breath samples were collected onto thermal desorption tubes using a portable breath collection unit. Samples were collected pre-exercise, and at 10 and 60 min following a maximal exercise test (VO2MAX). Breath VOCs were analysed by thermal desorption-gas chromatography-mass spectrometry using a non-targeted approach. Data showed a tendency for reduced isoprene in samples at 10 min post-exercise, with a return to baseline by 60 min. However, inter-individual variation meant differences between baseline and 10 min could not be confirmed, although the 10 and 60 min timepoints were different (p = 0.041). In addition, baseline samples showed a tendency for both acetone and isoprene to be reduced in those with higher absolute VO2MAX scores (mL(O2)/min), although with restricted statistical power. Baseline samples could not differentiate between relative VO2MAX scores (mL(O2)/kg/min). In conclusion, these data support that isoprene levels are dynamic in response to exercise.

Liming impacts barley yield over a wide concentration range of soil exchangeable cations.

Liming has widespread and significant impacts on soil processes and crop responses. The aim of this study was to describe the relationships between exchangeable cation concentrations in soil and the relative yield of spring barley. The hypothesis was that yield is restricted by the concentration of a single exchangeable cation in the soil. For simplicity, we focused on spring barley which was grown in nine years of a long-term experiment at two sites (Rothamsted and Woburn). Four liming rates were applied and in each year the relative yield (RY) and the concentrations of exchangeable cations were assessed. Liming had highly significant effects on the concentrations of most exchangeable cations, except for Cu and K. There were significant negative relationships (either linear or exponential) between the exchangeable concentrations of Mn, Cd, Cr, Al, Fe, Cu, Co, Zn and Ni in soil and soil pH. The relationships between RY and the concentrations of selected exchangeable cations (Mn, Ca and Al) were described well using log-logistic relationships. For these cations a significant site effect was probably due to fundamental differences in soil properties. At both sites the concentrations of exchangeable soil Al were excessive (> 7.5 mg kg-1) and were most likely responsible for reduced barley yields (where RY ≤ 0.5) with soil acidification. At Rothamsted barley yield was non-limited (where RY ≥ 1) at soil exchangeable Mn concentrations (up to 417 mg kg-1) greater than previously considered toxic, which requires further evaluation of critical Mn concentrations. SUPPLEMENTARY INFORMATION: The online version of this article (10.1007/s10705-020-10117-2) contains supplementary material, which is available to authorized users.

The variability of volatile organic compounds in the indoor air of clinical environments.

The development of clinical breath-analysis is confounded by the variability of background volatile organic compounds (VOCs). Reliable interpretation of clinical breath-analysis at individual, and cohort levels requires characterisation of clinical-VOC levels and exposures. Active-sampling with thermal-desorption/gas chromatography-mass spectrometry recorded and evaluated VOC concentrations in 245 samples of indoor air from three sites in a large National Health Service (NHS) provider trust in the UK over 27 months. Data deconvolution, alignment and clustering isolated 7344 features attributable to VOC and described the variability (composition and concentration) of respirable clinical VOC. 328 VOC were observed in more than 5% of the samples and 68 VOC appeared in more than 30% of samples. Common VOC were associated with exogenous and endogenous sources and 17 VOC were identified as seasonal differentiators. The presence of metabolites from the anaesthetic sevoflurane, and putative-disease biomarkers in room air, indicated that exhaled VOC were a source of background-pollution in clinical breath-testing activity. With the exception of solvents, and waxes associated with personal protective equipment (PPE), exhaled VOC concentrations above 3µg m-3are unlikely to arise from room air contamination, and in the absence of extensive survey-data, this level could be applied as a threshold for inclusion in studies, removing a potential environmental confounding-factor in developing breath-based diagnostics.

IABR Symposium 2021 meeting report: breath standardization, sampling, and testing in a time of COVID-19.

Due to COVID-19 travel disruptions, the International Association of Breath Research hosted the planned 2021 Breath Summit virtually as a symposium with oral and poster presentations. The event was comprised of a week-long social media asynchronous online event for sharing research abstracts, posters and discussions. Subsequently, there were two days of real-time webinar platform interactions each featuring three technical presentations, open forum questions, answers, and commentary. The symposium was well attended and well received. It allowed the breath community to share new research and to reconnect with colleagues and friends. This report presents an overview of the topics presented and various salient discussion points.

Advanced In Vitro Modeling to Study the Paradox of Mechanically Induced Cardiac Fibrosis.

In heart failure, cardiac fibrosis is the result of an adverse remodeling process. Collagen is continuously synthesized in the myocardium in an ongoing attempt of the heart to repair itself. The resulting collagen depositions act counterproductively, causing diastolic dysfunction and disturbing electrical conduction. Efforts to treat cardiac fibrosis specifically have not been successful and the molecular etiology is only partially understood. The differentiation of quiescent cardiac fibroblasts to extracellular matrix-depositing myofibroblasts is a hallmark of cardiac fibrosis and a key aspect of the adverse remodeling process. This conversion is induced by a complex interplay of biochemical signals and mechanical stimuli. Tissue-engineered 3D models to study cardiac fibroblast behavior in vitro indicate that cyclic strain can activate a myofibroblast phenotype. This raises the question how fibroblast quiescence is maintained in the healthy myocardium, despite continuous stimulation of ultimately profibrotic mechanotransductive pathways. In this review, we will discuss the convergence of biochemical and mechanical differentiation signals of myofibroblasts, and hypothesize how these affect this paradoxical quiescence. Impact statement Mechanotransduction pathways of cardiac fibroblasts seem to ultimately be profibrotic in nature, but in healthy human myocardium, cardiac fibroblasts remain quiescent, despite continuous mechanical stimulation. We propose three hypotheses that could explain this paradoxical state of affairs. Furthermore, we provide suggestions for future research, which should lead to a better understanding of fibroblast quiescence and activation, and ultimately to new strategies for the prevention and treatment of cardiac fibrosis and heart failure.

Volatile organic compounds in a headspace sampling system and asthmatics sputum samples.

The headspace of a biological sample contains exogenous volatile organic compounds (VOCs) present within the sampling environment which represent the background signal. This study aimed to characterise the background signal generated from a headspace sampling system in a clinical site, to evaluate intra- and inter-day variation of background VOC and to understand the impact of a sample itself upon commonly reported background VOC using sputum headspace samples from severe asthmatics. The headspace, in absence of a biological sample, was collected hourly from 11am to 3pm within a day (time of clinical samples acquisition), and from Monday to Friday in a week, and analysed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Chemometric analysis identified 1120 features, 37 of which were present in at least the 80% of all the samples. The analyses of intra- and inter-day background variations were performed on 13 of the most abundant features, ubiquitously present in headspace samples. The concentration ratios relative to background were reported for the selected abundant VOC in 36 asthmatic sputum samples, acquired from 36 stable severe asthma patients recruited at Glenfield Hospital, Leicester, UK. The results identified no significant intra- or inter-day variations in compounds levels and no systematic bias ofz-scores, with the exclusion of benzothiazole, whose abundance increased linearly between 11am and 3pm with a maximal intra-day fold change of 2.13. Many of the identified background features are reported in literature as components of headspace of biological samples and are considered potential biomarkers for several diseases. The selected background features were identified in headspace of all severe asthma sputum samples, albeit with varying levels of enrichment relative to background. Our observations support the need to consider the background signal derived from the headspace sampling system when developing and validating headspace biomarker signatures using clinical samples.

Diagnosis of COVID-19 by analysis of breath with gas chromatography-ion mobility spectrometry - a feasibility study.

BACKGROUND: There is an urgent need to rapidly distinguish COVID-19 from other respiratory conditions, including influenza, at first-presentation. Point-of-care tests not requiring laboratory- support will speed diagnosis and protect health-care staff. We studied the feasibility of using breath-analysis to distinguish these conditions with near-patient gas chromatography-ion mobility spectrometry (GC-IMS). METHODS: Independent observational prevalence studies at Edinburgh, UK, and Dortmund, Germany, recruited adult patients with possible COVID-19 at hospital presentation. Participants gave a single breath-sample for VOC analysis by GC-IMS. COVID-19 infection was identified by transcription polymerase chain reaction (RT- qPCR) of oral/nasal swabs together with clinical-review. Following correction for environmental contaminants, potential COVID-19 breath-biomarkers were identified by multi-variate analysis and comparison to GC-IMS databases. A COVID-19 breath-score based on the relative abundance of a panel of volatile organic compounds was proposed and tested against the cohort data. FINDINGS: Ninety-eight patients were recruited, of whom 21/33 (63.6%) and 10/65 (15.4%) had COVID-19 in Edinburgh and Dortmund, respectively. Other diagnoses included asthma, COPD, bacterial pneumonia, and cardiac conditions. Multivariate analysis identified aldehydes (ethanal, octanal), ketones (acetone, butanone), and methanol that discriminated COVID-19 from other conditions. An unidentified-feature with significant predictive power for severity/death was isolated in Edinburgh, while heptanal was identified in Dortmund. Differentiation of patients with definite diagnosis (25 and 65) of COVID-19 from non-COVID-19 was possible with 80% and 81.5% accuracy in Edinburgh and Dortmund respectively (sensitivity/specificity 82.4%/75%; area-under-the-receiver- operator-characteristic [AUROC] 0.87 95% CI 0.67 to 1) and Dortmund (sensitivity / specificity 90%/80%; AUROC 0.91 95% CI 0.87 to 1). INTERPRETATION: These two studies independently indicate that patients with COVID-19 can be rapidly distinguished from patients with other conditions at first healthcare contact. The identity of the marker compounds is consistent with COVID-19 derangement of breath-biochemistry by ketosis, gastrointestinal effects, and inflammatory processes. Development and validation of this approach may allow rapid diagnosis of COVID-19 in the coming endemic flu seasons. FUNDING: MR was supported by an NHS Research Scotland Career Researcher Clinician award. DMR was supported by the University of Edinburgh ref COV_29.

Breath markers for therapeutic radiation.

Radiation dose is important in radiotherapy. Too little, and the treatment is not effective, too much causes radiation toxicity. A biochemical measurement of the effect of radiotherapy would be useful in personalisation of this treatment. This study evaluated changes in exhaled breath volatile organic compounds (VOC) associated with radiotherapy with thermal desorption gas chromatography mass-spectrometry followed by data processing and multivariate statistical analysis. Further the feasibility of adopting gas chromatography ion mobility spectrometry for radiotherapy point-of-care breath was assessed. A total of 62 participants provided 240 end-tidal 1 dm3 breath samples before radiotherapy and at 1, 3, and 6 h post-exposure, that were analysed by thermal-desorption/gas-chromatography/quadrupole mass-spectrometry. Data were registered by retention-index and mass-spectra before multivariate statistical analyses identified candidate markers. A panel of sulfur containing compounds (thio-VOC) were observed to increase in concentration over the 6 h following irradiation. 3-methylthiophene (80 ng.m-3 to 790 ng.m-3) had the lowest abundance while 2-thiophenecarbaldehyde(380 ng.m-3 to 3.85 µg.m-3) the highest; note, exhaled 2-thiophenecarbaldehyde has not been observed previously. The putative tumour metabolite 2,4-dimethyl-1-heptene concentration reduced by an average of 73% over the same time. Statistical scoring based on the signal intensities thio-VOC and 3-methylthiophene appears to reflect individuals' responses to radiation exposure from radiotherapy. The thio-VOC are hypothesised to derive from glutathione and Maillard-based reactions and these are of interest as they are associated with radio-sensitivity. Further studies with continuous monitoring are needed to define the development of the breath biochemistry response to irradiation and to determine the optimum time to monitor breath for radiotherapy markers. Consequently, a single 0.5 cm3 breath-sample gas chromatography-ion mobility approach was evaluated. The calibrated limit of detection for 3-methylthiophene was 10 µg.m-3 with a lower limit of the detector's response estimated to be 210 fg.s-1; the potential for a point-of-care radiation exposure study exists.

A benchmarking protocol for breath analysis: the peppermint experiment.

Sampling of volatile organic compounds (VOCs) has shown promise for detection of a range of diseases but results have proved hard to replicate due to a lack of standardization. In this work we introduce the 'Peppermint Initiative'. The initiative seeks to disseminate a standardized experiment that allows comparison of breath sampling and data analysis methods. Further, it seeks to share a set of benchmark values for the measurement of VOCs in breath. Pilot data are presented to illustrate the standardized approach to the interpretation of results obtained from the Peppermint experiment. This pilot study was conducted to determine the washout profile of peppermint compounds in breath, identify appropriate sampling time points, and formalise the data analysis. Five and ten participants were recruited to undertake a standardized intervention by ingesting a peppermint oil capsule that engenders a predictable and controlled change in the VOC profile in exhaled breath. After collecting a pre-ingestion breath sample, five further samples are taken at 2, 4, 6, 8, and 10 h after ingestion. Samples were analysed using ion mobility spectrometry coupled to multi-capillary column and thermal desorption gas chromatography mass spectrometry. A regression analysis of the washout data was used to determine sampling times for the final peppermint protocol, and the time for the compound measurement to return to baseline levels was selected as a benchmark value. A measure of the quality of the data generated from a given technique is proposed by comparing data fidelity. This study protocol has been used for all subsequent measurements by the Peppermint Consortium (16 partners from seven countries). So far 1200 breath samples from 200 participants using a range of sampling and analytical techniques have been collected. The data from the consortium will be disseminated in subsequent technical notes focussing on results from individual platforms.

Risk Perception Plays Minimal Role in Sun Exposure Behaviours.

Despite decades of public health campaigns, tanning and sunburn still occur at unacceptably high rates. Skin cancer prevention campaigns predominately focus on increasing awareness of the risk of excessive sun exposure. This study sought to assess the efficacy of this approach, by interrogating correlations between risk perception and sun exposure behaviour. A 31-item questionnaire assessing skin cancer risk factors, tanning attitudes, sunburn and tanning behaviour was undertaken by individuals who attended a workplace skin check. Validated questions were included to assess cognitive and affective risk perception and to frame risk as absolute, comparative and conditional. One hundred sixty-seven respondents completed the questionnaire. No aspects of risk perception (absolute cognitive, affective or conditional) significantly correlated with protective sun exposure behaviour, with the exception of perceived comparative severity of skin cancer. Instead, positive tanning attitudes were far more significantly correlated with sun exposure behaviour. Actual risk and risk perception have very limited impact on sun exposure behaviour. Instead, sun exposure behaviour was significantly linked with positive tanning attitudes. It is suggested, therefore, that campaigns focussing solely on education regarding risk factors appear to have been ineffective in behaviour mitigation, and innovative approaches, aimed at influencing tanning norms, might complement the existing educational campaigns.

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

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

VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography/Mass Spectrometry Data.

Metabolic profiling of breath analysis involves processing, alignment, scaling, and clustering of thousands of features extracted from gas chromatography/mass spectrometry (GC/MS) data from hundreds of participants. The multistep data processing is complicated, operator error-prone, and time-consuming. Automated algorithmic clustering methods that are able to cluster features in a fast and reliable way are necessary. These accelerate metabolic profiling and discovery platforms for next-generation medical diagnostic tools. Our unsupervised clustering technique, VOCCluster, prototyped in Python, handles features of deconvolved GC/MS breath data. VOCCluster was created from a heuristic ontology based on the observation of experts undertaking data processing with a suite of software packages. VOCCluster identifies and clusters groups of volatile organic compounds (VOCs) from deconvolved GC/MS breath with similar mass spectra and retention index profiles. VOCCluster was used to cluster more than 15 000 features extracted from 74 GC/MS clinical breath samples obtained from participants with cancer before and after a radiation therapy. Results were evaluated against a panel of ground truth compounds and compared to other clustering methods (DBSCAN and OPTICS) that were used in previous metabolomics studies. VOCCluster was able to cluster those features into 1081 groups (including endogenous and exogenous compounds and instrumental artifacts) with an accuracy rate of 96% (±0.04 at 95% confidence interval).

Breath analysis by two-dimensional gas chromatography with dual flame ionisation and mass spectrometric detection - Method optimisation and integration within a large-scale clinical study.

Precision medicine has spurred new innovations in molecular pathology leading to recent advances in the analysis of exhaled breath as a non-invasive diagnostic tool. Volatile organic compounds (VOCs) detected in exhaled breath have the potential to reveal a wealth of chemical and metabolomic information. This study describes the development of a method for the analysis of breath, based on automated thermal desorption (TD) combined with flow modulated comprehensive two-dimensional gas chromatography (GC×GC) with dual flame ionisation and quadrupole mass spectrometric detection (FID and qMS). The constrained optimisation and analytical protocol was designed to meet the practical demands of a large-scale multi-site clinical study, while maintaining analytical rigour to produce high fidelity data. The results demonstrate a comprehensive method optimisation for the collection and analysis of breath VOCs by GC×GC, integral to the standardisation and integration of breath analysis within large clinical studies.

Risk stratification of symptomatic patients suspected of colorectal cancer using faecal and urinary markers.

AIM: Faecal markers, such as the faecal immunochemical test for haemoglobin (FIT) and faecal calprotectin (FCP), have been increasingly used to exclude colorectal cancer (CRC) and colonic inflammation. However, in those with lower gastrointestinal symptoms there are considerable numbers who have cancer but have a negative FIT test (i.e. false negative), which has impeded its use in clinical practice. We undertook a study of diagnostic accuracy CRC using FIT, FCP and urinary volatile organic compounds (VOCs) in patients with lower gastrointestinal symptoms. METHOD: One thousand and sixteen symptomatic patients with suspected CRC referred by family physicians were recruited prospectively in accordance with national referring protocol. A total of 562 patients who completed colonic investigations, in addition to providing stool for FIT and FCP as well as urine samples for urinary VOC measurements, were included in the final outcome measures. RESULTS: The sensitivity and specificity for CRC using FIT was 0.80 [95% confidence interval (CI) 0.66-0.93] and 0.93 (CI 0.91-0.95), respectively. For urinary VOCs, the sensitivity and specificity for CRC was 0.63 (CI 0.46-0.79) and 0.63 (CI 0.59-0.67), respectively. However, for those who were FIT-negative CRC (i.e. false negatives), the addition of urinary VOCs resulted in a sensitivity of 0.97 (CI 0.90-1.0) and specificity of 0.72 (CI 0.68-0.76). CONCLUSIONS: When applied to the FIT-negative group, urinary VOCs improve CRC detection (sensitivity rises from 0.80 to 0.97), thus showing promise as a second-stage test to complement FIT in the detection of CRC.

Discrimination of bacteria by rapid sensing their metabolic volatiles using an aspiration-type ion mobility spectrometer (a-IMS) and gas chromatography-mass spectrometry GC-MS.

The objective of our study was to investigate whether one may quickly and reliably discriminate different microorganism strains by direct monitoring of the headspace atmosphere above their cultures. Headspace samples above a series of in vitro bacterial cultures were directly interrogated using an aspiration type ion mobility spectrometer (a-IMS), which produced distinct profiles ("fingerprints") of ion currents generated simultaneously by the detectors present inside the ion mobility cell. Data processing and analysis using principal component analysis showed net differences in the responses produced by volatiles emitted by various bacterial strains. Fingerprint assignments were conferred on the basis of product ion mobilities; ions of differing size and mass were deflected in a different degree upon their introduction of a transverse electric field, impacting finally on a series of capacitors (denominated as detectors, or channels) placed in a manner analogous to sensor arrays. Three microorganism strains were investigated - Escherichia coli, Bacillus subtilis and Staphylococcus aureus; all strains possess a relatively low pathogenic character. Samples of air with a 5 cm3 volume from the headspace above the bacterial cultures in agar growth medium were collected using a gas-tight chromatographic syringe and injected inside the closed-loop pneumatic circuit of the breadboard a-IMS instrument model ChemPro-100i (Environics Oy, Finland), at a distance of about 1 cm from the ionization source. The resulting chemical fingerprints were produced within two seconds from the moment of injection. The sampling protocol involved to taking three replicate samples from each of 10 different cultures for a specific strain, during a total period of 72 h after the initial incubation - at 24, 48 and 72 h, respectively. Principal component analysis (PCA) was used to discriminate between the IMS fingerprints. PCA was found to successfully discriminate between bacteria at three levels in the experimental campaign: 1) between blank samples from growth medium and samples from bacterial cultures, 2) between samples from different bacterial strains, and 3) between time evolutions of headspace samples from the same bacterial strain over the 3-day sampling period. Consistent classification between growth medium samples and growth medium inoculated with bacteria was observed in both positive and negative detection/ionization modes. In parallel, headspace air samples of 1 dm3 were collected from each bacterial culture and loaded onto Tenax™-Carbograph desorption tubes, using a custom built sampling unit based on a portable sampling pump. One sample was taken for each of 10 different cultures of a strain, at 24, 48 and 72 h after the initial incubation. These adsorption tubes were subsequently analyzed using thermal desorption - gas chromatography - mass spectrometry (TD-GC-MS). This second dataset was intended to produce a qualitative analysis of the volatiles present in the headspace above the bacterial cultures.