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Paratuberculosis is an important disease of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). Early detection is crucial for successful infection control, but available diagnostic tests are still dissatisfying. Methods allowing a rapid, economic, and reliable identification of animals or herds affected by MAP are urgently required. This explorative study evaluated the potential of volatile organic compounds (VOCs) to discriminate between cattle with and without MAP infections. Headspaces above fecal samples and alveolar fractions of exhaled breath of 77 cows from eight farms with defined MAP status were analyzed in addition to stable air samples. VOCs were identified by GC–MS and quantified against reference substances. To discriminate MAP-positive from MAP-negative samples, VOC feature selection and random forest classification were performed. Classification models, generated for each biological specimen, were evaluated using repeated cross-validation. The robustness of the results was tested by predicting samples of two different sampling days. For MAP classification, the different biological matrices emitted diagnostically relevant VOCs of a unique but partly overlapping pattern (fecal headspace: 19, alveolar gas: 11, stable air: 4–5). Chemically, relevant compounds belonged to hydrocarbons, ketones, alcohols, furans, and aldehydes. Comparing the different biological specimens, VOC analysis in fecal headspace proved to be most reproducible, discriminatory, and highly predictive.

Analysis of volatile organic compounds (VOCs) is a novel approach to accelerate bacterial culture diagnostics of Mycobacterium avium subsp. paratuberculosis (MAP). In the present study, cultures of fecal and tissue samples from MAP-infected and non-suspect dairy cattle and goats were explored to elucidate the effects of sample matrix and of animal species on VOC emissions during bacterial cultivation and to identify early markers for bacterial growth. The samples were processed following standard laboratory procedures, culture tubes were incubated for different time periods. Headspace volume of the tubes was sampled by needle trap-micro-extraction, and analyzed by gas chromatography-mass spectrometry. Analysis of MAP-specific VOC emissions considered potential characteristic VOC patterns. To address variation of the patterns, a flexible and robust machine learning workflow was set up, based on random forest classifiers, and comprising three steps: variable selection, parameter optimization, and classification. Only a few substances originated either from a certain matrix or could be assigned to one animal species. These additional emissions were not considered informative by the variable selection procedure. Classification accuracy of MAP-positive and negative cultures of bovine feces was 0.98 and of caprine feces 0.88, respectively. Six compounds indicating MAP presence were selected in all four settings (cattle vs. goat, feces vs. tissue): 2-Methyl-1-propanol, 2-methyl-1-butanol, 3-methyl-1-butanol, heptanal, isoprene, and 2-heptanone. Classification accuracies for MAP growth-scores ranged from 0.82 for goat tissue to 0.89 for cattle feces. Misclassification occurred predominantly between related scores. Seventeen compounds indicating MAP growth were selected in all four settings, including the 6 compounds indicating MAP presence. The concentration levels of 2,3,5-trimethylfuran, 2-pentylfuran, 1-propanol, and 1-hexanol were indicative for MAP cultures before visible growth was apparent. Thus, very accurate classification of the VOC samples was achieved and the potential of VOC analysis to detect bacterial growth before colonies become visible was confirmed. These results indicate that diagnosis of paratuberculosis can be optimized by monitoring VOC emissions of bacterial cultures. Further validation studies are needed to increase the robustness of indicative VOC patterns for early MAP growth as a pre-requisite for the development of VOC-based diagnostic analysis systems.

Malignant diseases can cause tumor-associated cachexia (TAC). Supplementation with prebiotic non-digestible carbohydrates exerts positive metabolic effects in experimental oncologic diseases. The aim of this project was to assess the effect of prebiotic supplementation with OMNi-LOGiC&reg, FIBRE on intestinal microbiome, bacterial metabolism, gut permeability, and inflammation in a murine model of neuroblastoma (NB)-associated TAC. For this study, 2,000,000 NB cells (MHH-NB11) were implanted into athymic mice followed by daily supplementation with water or 200 mg prebiotic oligosaccharide (POS) OMNi-LOGiC&reg, FIBRE (NB-Aqua, n = 12, NB-POS, n = 12). Three animals of each tumor group did not develop NB. The median time of tumor growth (first visibility to euthanasia) was 37 days (IQR 12.5 days) in the NB-Aqua group and 37 days (IQR 36.5 days) in the NB-POS group (p = 0.791). At euthanasia, fecal microbiome and volatile organic compounds (VOCs), gut permeability (fluorescein isothiocyanate-dextran (FITC-dextran), and gut barrier markers were measured. Values were compared to sham animals following injection of culture medium and gavage of either water or OMNi-LOGiC&reg, FIBRE (SH-Aqua, n = 10, SH-POS, n = 10). Alpha diversity did not differ significantly between the groups. Principal coordinate analysis (PCoA) revealed clustering differences between Aqua and POS animals. Both NB and POS supplementation led to taxonomic alterations of the fecal microbiome. Of 49 VOCs, 22 showed significant differences between the groups. NB animals had significantly higher gut permeability than Aqua animals, POS did not ameliorate these changes. The pore and leak pathways of tight junctions did not differ between groups. In conclusion, our results suggest that NB-induced TAC causes increased gut permeability coupled with compositional changes in the fecal microbiome and VOC profile. Prebiotic supplementation with OMNi-LOGiC&reg, FIBRE seemed to induce modifications of the fecal microbiome and VOC profile but did not improve gut permeability.

Volatile organic compounds (VOCs) emitted from breath, faeces or skin may reflect physiological and pathological processes in vivo. Our setup employs real-time proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS) to explore VOC emissions of dairy cows in stable air under field conditions. Within one herd of 596 cows, seven groups (8-117 cows per group) were assessed. Groups differed in milk yield and health status (two contained cows with paratuberculosis, a chronic intestinal infection). Each group arrived one after another in the area of air measurement in front of the milking parlour. A customised PTR-TOF-MS system with a 6 m long and heated transfer line, was used for measuring VOCs continuously for 7 h, 1.5 m above the cows. Three consecutive time periods were investigated. Twenty-seven VOCs increased while the animals were gathering in the waiting area, and decreased when the animals entered the milking parlour. Linear correlations between the number of animals present and VOC concentrations were found for (C4H6)H+ and (C3H6O)H+. A relatively high concentration of acetone above the cows that had recently given birth to a calf might be related to increased fat turnover due to calving and different nutrition. Changes in VOC emissions were related to the presence of animals with paratuberculosis, to different average milk yields per group and to the time of the day (morning versus noon milking time). We found that VOC monitoring of stable air may provide additional immediate information on an animal's metabolic or health status and foster novel applications in the field of breath research.