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Social arthropods such as termites, ants, and bees are among others the most successful animal groups on earth. However, social arthropods face an elevated risk of infections due to the dense colony structure, which facilitates pathogen transmission. An interesting hypothesis is that social arthropods are protected by chemical compounds produced by the arthropods themselves, microbial symbionts, or plants they associate with. Stegodyphus dumicola is an African social spider species, inhabiting communal silk nests. Because of the complex three-dimensional structure of the spider nest antimicrobial volatile organic compounds (VOCs) are a promising protection against pathogens, because of their ability to diffuse through air-filled pores. We analyzed the volatilomes of S. dumicola, their nests, and capture webs in three locations in Namibia and assessed their antimicrobial potential. Volatilomes were collected using polydimethylsiloxane (PDMS) tubes and analyzed using GC/Q-TOF. We showed the presence of 199 VOCs and tentatively identified 53 VOCs. More than 40% of the tentatively identified VOCs are known for their antimicrobial activity. Here, six VOCs were confirmed by analyzing pure compounds namely acetophenone, 1,3-benzothiazole, 1-decanal, 2-decanone, 1-tetradecene, and docosane and for five of these compounds the antimicrobial activity were proven. The nest and web volatilomes had many VOCs in common, whereas the spider volatilomes were more differentiated. Clear differences were identified between the volatilomes from the different sampling sites which is likely justified by differences in the microbiomes of the spiders and nests, the plants, and the different climatic conditions. The results indicate the potential relevance of the volatilomes for the ecological success of S. dumicola.
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.