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Gram-negative bacteria expressing extended-spectrum [beta]-lactamases (ESBL) have emerged worldwide. ESBL colonisation can persist for years and may favour ESBL transmission. Interventions include contact isolation precautions and restriction of antibiotic use, but decolonisation (DC) for ESBL is not established. We performed a prospective controlled open-label cohort-study from 1/2000 to 1/2008 to determine the effectiveness of a standardised DC programme. ESBL-positive patients routinely underwent screening from rectum, throat, and urine. DC included: chlorhexidine 0.2% mouth rinse three times daily (throat colonisation), paromomycin 4x1g daily (intestinal colonisation), and oral antibiotics for urinary tract colonisation. ESBL elimination was defined as >=1 set of negative follow-up screenings (throat, rectal, urine). Of 100 enrolled patients, 83% of patients were infected and 17% colonised with ESBL. Escherichia coli (71%) and Klebsiella pneumoniae (25%) were the most frequent pathogens. Overall, 76% (76/100) of patients became negative for ESBL at follow-up. Fifty-five percent (42/76) of the successfully treated patients received systemic treatment for infection. Of those who completed DC, 83% (15/18) were free of ESBL at follow-up. DC success correlated with the number of risk factors and colonised sites. DC may be beneficial in a selected group of patients, potentially shortening duration of ESBL colonisation and subsequently reducing the risk for transmission. [ABSTRACT FROM AUTHOR]

Abstract Background Burkholderia pseudomallei, the etiologic agent of melioidosis, is endemic to tropic regions, mainly in Southeast Asia and northern Australia. Melioidosis occurs only sporadically in travellers returning from disease-endemic areas. Severe clinical disease is seen mostly in patients with alteration of immune status. In particular, pericardial effusion occurs in 1-3% of patients with melioidosis, confined to endemic regions. To our best knowledge, this is the first reported case of melioidosis in a traveller complicated by a hemodynamically significant pericardial effusion without predisposing disease. Case presentation A 44-year-old Caucasian man developed pneumonia, with bilateral pleural effusions and complicated by a hemodynamically significant pericardial effusion, soon after his return from Thailand to Switzerland. Cultures from different specimens including blood cultures turned out negative. Diagnosis was only accomplished by isolation of Burkholderia pseudomallei from the pericardial aspirate, thus finally enabling the adequate antibiotic treatment. Conclusions Melioidosis is a great mimicker and physicians in non-endemic countries should be aware of its varied manifestations. In particular, melioidosis should be considered in differential diagnosis of pericardial effusion in travellers , even without risk factors predisposing to severe disease.

We developed a novel approach to selectively isolate or remove nearly any compound from complex mixtures of volatile organic compounds. This was achieved by customizing a GC×GC system with a Deans switch, a passive splitter, and a custom-made adapter for sample recollection. The new setup was evaluated with 106 standard chemicals covering a wide range of volatility (boiling points: 56 - 343 ⁰C) and polarity (log P: 0.2 - 9.4). The method was used to remove two notorious malodorous compounds from spoiled wine samples. We found that the recovery can be maximized if a custom-made adapter is attached directly on the flame ionization detector port (average recovery rate of 76 ± 7 % for the standards). Eventually, we could selectively isolate or remove chemicals with peaks separated by a minimum distance of 50 ms for the second column throughout the whole chromatographic run. The developed system is expected to mainly be used in the field of flavor and fragrance analysis (i.e., selection of flavors and odorants of interest or removal of off-flavor or malodorous compounds). At present, we can reasonably collect about 100 ng of each single compound and are currently working on sample enrichment to improve our method to isolate sufficient amounts for further chemical analysis (e.g. high sensitivity nuclear magnetic resonance or chemical ionization tandem mass spectrometry)., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Matyas Ripszam, Federico Vivaldi, Tobias Bruderer, Fabio Di Francesco has patent #23,163,823.0, 2023 March 2023 pending to Italy/Pisa Patent. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

This paper describes the AEOLUS pilot study which combines breath analysis with cardiopulmonary exercise testing (CPET) and an echocardiographic examination for monitoring heart failure (HF) patients. Ten consecutive patients with a prior clinical diagnosis of HF with reduced left ventricular ejection fraction were prospectively enrolled together with 15 control patients with cardiovascular risk factors, including hypertension, type II diabetes or chronic ischemic heart disease. Breath samples were collected at rest and during CPET coupled with exercise stress echocardiography (CPET-ESE) protocol by means of needle trap micro-extraction and were analyzed through gas-chromatography coupled with mass spectrometry. The protocol also involved using of a selected ion flow tube mass spectrometer for a breath-by-breath isoprene and acetone analysis during exercise. At rest, HF patients showed increased breath levels of acetone and pentane, which are related to altered oxidation of fatty acids and oxidative stress, respectively. A significant positive correlation was observed between acetone and the gold standard biomarker NT-proBNP in plasma ( r = 0.646, p < 0.001), both measured at rest. During exercise, some exhaled volatiles (e.g., isoprene) mirrored ventilatory and/or hemodynamic adaptation, whereas others (e.g., sulfide compounds and 3-hydroxy-2-butanone) depended on their origin. At peak effort, acetone levels in HF patients differed significantly from those of the control group, suggesting an altered myocardial and systemic metabolic adaptation to exercise for HF patients. These preliminary data suggest that concomitant acquisition of CPET-ESE and breath analysis is feasible and might provide additional clinical information on the metabolic maladaptation of HF patients to exercise. Such information may refine the identification of patients at higher risk of disease worsening., (Creative Commons Attribution license.)

A key issue in GCxGC-HRMS data analysis is how to approach large-sample studies in an efficient and comprehensive way. We have developed a semi-automated data-driven workflow from identification to suspect screening, which allows highly selective monitoring of each identified chemical in a large-sample dataset. The example dataset used to illustrate the potential of the approach consisted of human sweat samples from 40 participants, including field blanks (80 samples). These samples have been collected in a Horizon 2020 project to investigate the capacity of body odour to communicate emotion and influence social behaviour. We used dynamic headspace extraction, which allows comprehensive extraction with high preconcentration capability, and has to date only been used for a few biological applications. We were able to detect a set of 326 compounds from a diverse range of chemical classes (278 identified compounds, 39 class unknowns, and 9 true unknowns). Unlike partitioning-based extraction methods, the developed method detects semi-polar (log P < 2) nitrogen and oxygen-containing compounds. However, it is unable to detect certain acids due to the pH conditions of unmodified sweat samples. We believe that our framework will open up the possibility of efficiently using GCxGC-HRMS for large-sample studies in a wide range of applications such as biological and environmental studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier B.V.)

The early detection of inflammation and infection is important to prevent irreversible lung damage in cystic fibrosis. Novel and non-invasive monitoring tools would be of high benefit for the quality of life of patients. Our group previously detected over 100 exhaled mass-to-charge ( m / z ) features, using on-line secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS), which distinguish children with cystic fibrosis from healthy controls. The aim of this study was to annotate as many m / z features as possible with putative chemical structures. Compound identification was performed by applying a rigorous workflow, which included the analysis of on-line MS 2 spectra and a literature comparison. A total of 49 discriminatory exhaled compounds were putatively identified. A group of compounds including glycolic acid, glyceric acid and xanthine were elevated in the cystic fibrosis group. A large group of acylcarnitines and aldehydes were found to be decreased in cystic fibrosis. The proposed compound identification workflow was used to identify signatures of volatile organic compounds that discriminate children with cystic fibrosis from healthy controls, which is the first step for future non-invasive and personalized applications.

Identifying and differentiating bacteria based on their emitted volatile organic compounds (VOCs) opens vast opportunities for rapid diagnostics. Secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) is an ideal technique for VOC-biomarker discovery because of its speed, sensitivity towards polar molecules and compound characterization possibilities. Here, an in vitro SESI-HRMS workflow to find biomarkers for cystic fibrosis (CF)-related pathogens P. aeruginosa , S. pneumoniae , S. aureus , H. influenzae , E. coli and S. maltophilia is described. From 180 headspace samples, the six pathogens are distinguishable in the first three principal components and predictive analysis with a support vector machine algorithm using leave-one-out cross-validation exhibited perfect accuracy scores for the differentiation between the groups. Additionally, 94 distinctive features were found by recursive feature elimination and further characterized by SESI-MS/MS, which yielded 33 putatively identified biomarkers. In conclusion, the six pathogens can be distinguished in vitro based on their VOC profiles as well as the herein reported putative biomarkers. In the future, these putative biomarkers might be helpful for pathogen detection in vivo based on breath samples from patients with CF.

In this study, a secondary electrospray ionization-high resolution mass spectrometer (SESI-HRMS) system was employed to profile the real-time exhaled metabolome of ten subjects who had ingested a peppermint oil capsule. In total, six time points were sampled during the experiment. Using an untargeted way of profiling breath metabolome, 2333 m/z unique metabolite features were determined in positive mode, and 1322 in negative mode. To benchmark the performance of the SESI-HRMS setup, several additional checks were done, including determination of the technical variation, the biological variation of one subject within three days, the variation within a time point, and the variation across all samples, taking all m/z features into account. Reproducibility was good, with the median technical variation being ∼ 18% and the median variation within biological replicates being ∼ 34%. Both variations were lower than the variation across individuals. Washout profiles of compounds from the peppermint oil, including menthone, limonene, pulegone, menthol and menthofuran were determined in all subjects. Metabolites of the peppermint oil were also determined in breath, for example, cis/trans-carveol, perillic acid and menthol glucuronide. Butyric acid was found to be the major metabolite that reduce the uptake rate of limonene. Pathways related to limonene metabolism were examined, and meaningful pathways were identified from breath metabolomics data acquired by SESI using an untargeted analysis., (© 2021 IOP Publishing Ltd.)

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

Early pulmonary infection and inflammation result in irreversible lung damage and are major contributors to cystic fibrosis (CF)-related morbidity. An easy to apply and noninvasive assessment for the timely detection of disease-associated complications would be of high value. We aimed to detect volatile organic compound (VOC) breath signatures of children with CF by real-time secondary electrospray ionisation high-resolution mass spectrometry (SESI-HRMS). A total of 101 children, aged 4-18 years (CF=52; healthy controls=49) and comparable for sex, body mass index and lung function were included in this prospective cross-sectional study. Exhaled air was analysed by a SESI-source linked to a high-resolution time-of-flight mass spectrometer. Mass spectra ranging from m/z 50 to 500 were recorded. Out of 3468 m/z features, 171 were significantly different in children with CF (false discovery rate adjusted p-value of 0.05). The predictive ability (CF versus healthy) was assessed by using a support-vector machine classifier and showed an average accuracy (repeated cross-validation) of 72.1% (sensitivity of 77.2% and specificity of 67.7%). This is the first study to assess entire breath profiles of children with SESI-HRMS and to extract sets of VOCs that are associated with CF. We have detected a large set of exhaled molecules that are potentially related to CF, indicating that the molecular breath of children with CF is diverse and informative., Competing Interests: Conflict of interest: Ronja Weber has nothing to disclose. Conflict of interest: N. Haas has nothing to disclose. Conflict of interest: A. Baghdasaryan has nothing to disclose. Conflict of interest: T. Bruderer has nothing to disclose. Conflict of interest: D. Inci has nothing to disclose. Conflict of interest: S. Micic has nothing to disclose. Conflict of interest: N. Perkins has nothing to disclose. Conflict of interest: R. Spinas has nothing to disclose. Conflict of interest: R. Zenobi has nothing to disclose. Conflict of interest: A. Moeller has nothing to disclose., (Copyright ©ERS 2020.)

On-line analysis of exhaled breath offers insight into a person's metabolism without the need for sample preparation or sample collection. Due to its noninvasive nature and the possibility to sample continuously, the analysis of breath has great clinical potential. The unique features of this technology make it an attractive candidate for applications in medicine, beyond the task of diagnosis. We review the current methodologies for on-line breath analysis, discuss current and future applications, and critically evaluate challenges and pitfalls such as the need for standardization. Special emphasis is given to the use of the technology in diagnosing respiratory diseases, potential niche applications, and the promise of breath analysis for personalized medicine. The analytical methodologies used range from very small and low-cost chemical sensors, which are ideal for continuous monitoring of disease status, to optical spectroscopy and state-of-the-art, high-resolution mass spectrometry. The latter can be utilized for untargeted analysis of exhaled breath, with the capability to identify hitherto unknown molecules. The interpretation of the resulting big data sets is complex and often constrained due to a limited number of participants. Even larger data sets will be needed for assessing reproducibility and for validation of biomarker candidates. In addition, molecular structures and quantification of compounds are generally not easily available from on-line measurements and require complementary measurements, for example, a separation method coupled to mass spectrometry. Furthermore, a lack of standardization still hampers the application of the technique to screen larger cohorts of patients. This review summarizes the present status and continuous improvements of the principal on-line breath analysis methods and evaluates obstacles for their wider application.

Background: Exacerbations of COPD are defined by acute worsening of respiratory symptoms leading to a change in therapy. Identifying altered metabolic processes in patients at risk for future exacerbations is desirable for treatment optimization, the development of new therapeutic strategies, and perhaps diagnostic value. We aimed to identify affected pathways using the profiles of volatile organic compounds in exhaled breath from patients with COPD with and without frequent exacerbations (≥ 2 exacerbations within the past 12 months)., Methods: In this matched cohort study, exhaled breath profiles from patients with COPD and frequent exacerbations ("frequent exacerbators") and without frequent exacerbations ("nonfrequent exacerbators") were analyzed during an exacerbation-free interval using real-time secondary electrospray ionization high-resolution mass spectrometry. We analyzed exhaled breath from 26 frequent exacerbators and 26 nonfrequent exacerbators that were matched in terms of age, sex, and smoking history. To obtain new pathophysiological insights, we investigated significantly altered metabolites, which can be assigned to specific pathways. Metabolites were identified by using a Wilcoxon rank-sum test., Results: Metabolite levels from the ω-oxidation pathway, namely ω-hydroxy, ω-oxo, and dicarboxylic acids, were consistently decreased in frequent exacerbators. Additionally, several new nitro-aromatic metabolites, which were significantly increased in frequent exacerbators, were identified., Conclusions: Real-time breath analysis by secondary electrospray high-resolution mass spectrometry allows molecular profiling of exhaled breath, providing insights about ongoing biochemical processes in patients with COPD at risk for exacerbations., Trial Registry: ClinicalTrials.gov; No.: NCT02186639; URL: www.clinicaltrials.gov., (Copyright © 2019 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.)

Background and Objective: Diagnosis of idiopathic pulmonary fibrosis (IPF) is complex and its pathogenesis is poorly understood. Recent findings indicate elevated levels of proline and other amino acids in lung tissue of IPF patients which may also be of diagnostic value. Following these findings, we hypothesized that such altered metabolic profiles would be mirrored in exhaled breath and could therefore be captured non-invasively in real time., Methods: We aimed to validate these results using real-time exhaled breath analysis by secondary electrospray ionization-mass spectrometry, which can provide a non-invasive, painless and fast insight into the metabolism. Breath analysis was performed in a matched 1:1 case-control study involving 21 patients with IPF and 21 control subjects., Results: We found significantly (P < 0.05) elevated levels of proline, 4-hydroxyproline, alanine, valine, leucine/isoleucine and allysine in breath of IPF patients, whereas pyroglutamic acid and phenylalanine did not show significant differences. This coincides with the amino acid's abundance in pulmonary tissue indicating that our observations reflect progressing fibrosis. In addition, amino acid levels correlated across subjects, further supporting a common underlying pathway. We were able to obtain a cross-validated area under the curve of 0.86, suggesting that these increased amino acid levels in exhaled breath have the potential to be used as biomarkers for IPF., Conclusion: We could validate previous findings of elevated lung tissue amino acid levels in IPF and show that online breath analysis might be a practical tool for a rapid screening for IPF., (© 2019 Asian Pacific Society of Respirology.)

It has been shown that bacteria in periodontally diseased patients can be recognized by the detection of volatile metabolites in the headspace of saliva by real-time ambient mass spectrometry. The aim of this study was to use this detection method to analyze the oral metabolome in diseased periodontitis patients before and after therapy to monitor disease evolution and healing events. Twelve patients with advanced chronic periodontal disease and 12 periodontally healthy controls served as test and control groups, respectively. Clinical data, subgingival plaque samples and saliva samples were collected at baseline (BL) and 3 months after treatment. The test group received non-surgical scaling and root planing using systemic antibiotics and the control group received one session of supragingival cleaning. Saliva samples from all subjects were analyzed with ambient mass spectrometry. Significant metabolic alterations were found in the headspace of saliva of periodontitis patients 3 months after the non-surgical periodontal treatment. Furthermore, the diseased group showed metabolic features after the treatment that were similar to the healthy control group. In addition, 29 metabolic features correlated with A. actinomycetemcomitans , 17 features correlated with P. gingivalis and one feature correlated with T. denticola . It was shown that headspace secondary electrospray ionization - mass spectrometry allows the detection of different volatile metabolites in healthy and diseased patients. It can be concluded that this rapid and minimally invasive method could have the potential to routinely diagnose and monitor periodontal diseases in the headspace of saliva samples and, eventually, in exhaled breath., (© 2019 The Association for Mass Spectrometry: Applications to the Clinical Lab (MSACL). Published by Elsevier B.V.)

The tricarboxylic acid (TCA) cycle is one of the most important metabolic pathway for cellular respiration in aerobic organisms. It provides and collects intermediates for many other interconnecting pathways and acts as a hub connecting metabolism of carbohydrates, fatty acids, and amino acids. Alteration in intracellular levels of its intermediates has been linked with a wide range of illnesses ranging from cancer to cellular necrosis or liver cirrhosis. Therefore, there exists an intrinsic interest in monitoring such metabolites. Our goal in this study was to evaluate whether, at least the most volatile metabolites of the TCA cycle, could be detected in breath in vivo and in real time. We used secondary electrospray ionization coupled with high-resolution mass spectrometry (SESI-HRMS) to conduct this targeted analysis. We enrolled six healthy individuals who provided full exhalations into the SESI-HRMS system at different times during 3 days. For the first time, we observed exhaled compounds that appertain to the TCA cycle: fumaric, succinic, malic, keto-glutaric, oxaloacetic, and aconitic acids. We found high intraindividual variability and a significant overall difference between morning and afternoon levels for malic acid, oxaloacetic acid, and aconitic acid, supporting previous studies suggesting circadian fluctuations of these metabolites in humans. This study provides first evidence that TCA cycle could conveniently be monitored in breath, opening new opportunities to study in vivo this important metabolic pathway.

Objectives: Breakthrough candidemia (BTC) on fluconazole was associated with non-susceptible Candida spp. and increased mortality. This nationwide FUNGINOS study analyzed clinical and mycological BTC characteristics., Methods: A 3-year prospective study was conducted in 567 consecutive candidemias. Species identification and antifungal susceptibility testing (CLSI) were performed in the FUNGINOS reference laboratory. Data were analyzed according to STROBE criteria., Results: 43/576 (8%) BTC occurred: 37/43 (86%) on fluconazole (28 prophylaxis, median 200 mg/day). 21% BTC vs. 23% non-BTC presented severe sepsis/septic shock. Overall mortality was 34% vs. 32%. BTC was associated with gastrointestinal mucositis (multivariate OR 5.25, 95%CI 2.23-12.40, p < 0.001) and graft-versus-host-disease (6.25, 1.00-38.87, p = 0.05), immunosuppression (2.42, 1.03-5.68, p = 0.043), and parenteral nutrition (2.87, 1.44-5.71, p = 0.003). Non-albicans Candida were isolated in 58% BTC vs. 35% non-BTC (p = 0.005). 63% of 16 BTC occurring after 10-day fluconazole were non-susceptible (Candida glabrata, Candida krusei, Candida norvegensis) vs. 19% of 21 BTC (C. glabrata) following shorter exposure (7.10, 1.60-31.30, p = 0.007). Median fluconazole MIC was 4 mg/l vs. 0.25 mg/l (p < 0.001). Ten-day fluconazole exposure predicted non-susceptible BTC with 73% accuracy., Conclusions: Outcomes of BTC and non-BTC were similar. Fluconazole non-susceptible BTC occurred in three out of four cases after prolonged low-dose prophylaxis. This implies reassessment of prophylaxis duration and rapid de-escalation of empirical therapy in BTC after short fluconazole exposure., (Copyright © 2018 The British Infection Association. Published by Elsevier Ltd. All rights reserved.)

We aimed at defining profiles of volatile organic compounds in exhaled breath from patients with cystic fibrosis (CF) using a novel real-time mass spectrometry technique. In this prospective matched case-control study, 30 patients with CF, and 30 healthy control subjects were matched one-to-one according to age, gender, and smoking state. We performed exhaled breath analysis by untargeted secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS). Patients with CF (mean age 26.0 ± 13.0 years) and controls (mean age 27.9 ± 14.0 years) were analyzed using SESI-HRMS. 49 exhaled breath features were found to be altered (p-value < 0.05/q-value < 0.1) in CF patients, in comparison to healthy controls. The two most discriminating features showed a prediction AUROC of 77.1% (95% CI 62.2%-87.8%) with a specificity of 80.0% and a sensitivity of 63.3%. Levels of oxidative stress metabolites such as fatty acids were found to differ significantly between patients with CF and healthy controls. Furthermore, in patients with CF, 11 features correlated with the mucus concentration of Stenotrophomonas maltophilia bacteria. Exhaled breath analysis with SESI-HRMS allows the identification of CF specific compounds in real-time and may trace bacterial strains in affected patients with CF.

In the original publication the members of the FUNGINOS network were provided in such a way that they could not be indexed as collaborators on PubMed.

High-quality mass spectral libraries have become crucial in mass spectrometry-based metabolomics. Here, we investigate a workflow to generate accurate mass discrete and composite spectral libraries for metabolite identification and for SWATH mass spectrometry data processing. Discrete collision energy (5-100 eV) accurate mass spectra were collected for 532 metabolites from the human metabolome database (HMDB) by flow injection analysis and compiled into composite spectra over a large collision energy range (e.g., 10-70 eV). Full scan response factors were also calculated. Software tools based on accurate mass and predictive fragmentation were specially developed and found to be essential for construction and quality control of the spectral library. First, elemental compositions constrained by the elemental composition of the precursor ion were calculated for all fragments. Secondly, all possible fragments were generated from the compound structure and were filtered based on their elemental compositions. From the discrete spectra, it was possible to analyze the specific fragment form at each collision energy and it was found that a relatively large collision energy range (10-70 eV) gives informative MS/MS spectra for library searches. From the composite spectra, it was possible to characterize specific neutral losses as radical losses using in silico fragmentation. Radical losses (generating radical cations) were found to be more prominent than expected. From 532 metabolites, 489 provided a signal in positive mode [M+H] + and 483 in negative mode [M-H] - . MS/MS spectra were obtained for 399 compounds in positive mode and for 462 in negative mode; 329 metabolites generated suitable spectra in both modes. Using the spectral library, LC retention time, response factors to analyze data-independent LC-SWATH-MS data allowed the identification of 39 (positive mode) and 72 (negative mode) metabolites in a plasma pool sample (total 92 metabolites) where 81 previously were reported in HMDB to be found in plasma. Graphical abstract Library generation workflow for LC-SWATH MS, using collision energy spread, accurate mass, and fragment annotation.

The application of predicted LC retention time to support metabolite identification was evaluated for a metabolomics MS/MS database containing 532 compounds representative for the major human metabolite classes. LC retention times could be measured for two C18 type columns using a mobile phase of pH=3.0 for positive ESI mode (n=337, 228) and pH=8.0 for negative ESI mode (n=410, 233). A QSRR modelling was applied with a small set of model compound selected based on the Kennard-Stone algorithm. The models were implemented in the R environment and can be applied to any library. The prediction model was built with two molecular descriptors, LogD2 and the molecular volume. A limited set of model compounds (LC CalMix, n=16) could be validated on two different C18 reversed phase LC columns and with comparable prediction accuracy. The CalMix can be used to compensate for different LC systems. In addition, LC retention prediction was found, in combination with SWATH-MS, to be attractive to eliminate false positive identification as well as for ranking purpose different metabolite isomeric forms., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Omega-oxidation is a fatty acid degradation pathway that can occur alternatively to the dominant β-oxidation. The dysregulation of fatty acid oxidation has been related with a variety of diseases, termed fatty acid oxidation disorders. This work shows evidence for real-time detection in exhaled breath of the complete series of saturated linear ω-hydroxyalkanoic acids, ω-oxoalkanoic acids, and alkanedioic acids with carbon chain lengths of 5-15. We present a comprehensive analytical workflow using online and subsequent offline methods: secondary electrospray ionization mass spectrometry of exhaled breath and UHPLC-HRMS/MS experiments using exhaled breath condensate, respectively. By analyzing online breath measurements of 146 healthy individuals, we were able to obtain strong evidence for the correlation of these metabolite families. This enabled us to monitor the full ω-oxidation pathway in human exhaled breath. We could unambiguously identify these compounds, many of which have never been reported in breath so far. This comprehensive study on breath metabolites reinforces the notion of breath as a valuable source of information, which is underexploited in metabolomics.

We explore whether real-time breath analysis by high resolution mass spectrometry is suitable to monitor changes at the metabolic level due to inhaling bronchodilator medication. We compared the breath levels of metabolites in a group of patients (n = 50) at baseline and 10 and 30 min after inhalation of 200 μg salbutamol. The same procedure was performed with a group of controls (n = 48) inhaling a placebo spray. A total of 131 mass spectral features were significantly altered as a result of inhaling medication, but not after inhaling placebo. We found that homologous series of chemical classes correlated strongly with each other, strengthening the notion that certain biochemical processes can be monitored. For example, a series of fatty acids was found to be increased after salbutamol intake, suggesting lipolysis stimulation. Peaks corresponding to salbutamol, its main metabolite salbutamol-4-O-sulfate and formoterol were found to be generally increased in patients inhaling the drugs on an as-needed basis, as compared to non-medicated volunteers. Overall, these results suggest such real-time breath analysis is a useful tool for non-invasive therapeutic drug monitoring.

Immigrants from regions with a high incidence of tuberculosis (TB) are a risk group for TB in low-incidence countries such as Switzerland. In a previous analysis of a nationwide collection of 520 Mycobacterium tuberculosis isolates from 2000 to 2008, we identified 35 clusters comprising 90 patients based on standard genotyping (24-locus mycobacterial interspersed repetitive-unit-variable-number tandem-repeat [MIRU-VNTR] typing and spoligotyping). Here, we used whole-genome sequencing (WGS) to revisit these transmission clusters. Genome-based transmission clusters were defined as isolate pairs separated by ≤12 single nucleotide polymorphisms (SNPs). WGS confirmed 17/35 (49%) MIRU-VNTR typing clusters; the other 18 clusters contained pairs separated by >12 SNPs. Most transmission clusters (3/4) of Swiss-born patients were confirmed by WGS, as opposed to 25% (4/16) of the clusters involving only foreign-born patients. The overall clustering proportion was 17% (90 patients; 95% confidence interval [CI], 14 to 21%) by standard genotyping but only 8% (43 patients; 95% CI, 6 to 11%) by WGS. The clustering proportion was 17% (67/401; 95% CI, 13 to 21%) by standard genotyping and 7% (26/401; 95% CI, 4 to 9%) by WGS among foreign-born patients and 19% (23/119; 95% CI, 13 to 28%) and 14% (17/119; 95% CI, 9 to 22%), respectively, among Swiss-born patients. Using weighted logistic regression, we found weak evidence of an association between birth origin and transmission (adjusted odds ratio of 2.2 and 95% CI of 0.9 to 5.5 comparing Swiss-born patients to others). In conclusion, standard genotyping overestimated recent TB transmission in Switzerland compared to WGS, particularly among immigrants from regions with a high TB incidence, where genetically closely related strains often predominate. We recommend the use of WGS to identify transmission clusters in settings with a low incidence of TB., (Copyright © 2016, American Society for Microbiology. All Rights Reserved.)