Publications

@article{MUROVEC2018428,

title = {1H NMR metabolomics of microbial metabolites in the four MW agricultural biogas plant reactors: A case study of inhibition mirroring the acute rumen acidosis symptoms},

author = {Boštjan Murovec and Damjan Makuc and Sabina Kolbl Repinc and Zala Prevoršek and Domen Zavec and Robert Šket and Klemen Pečnik and Janez Plavec and Blaž Stres},

url = {http://www.sciencedirect.com/science/article/pii/S0301479718305991},

doi = {https://doi.org/10.1016/j.jenvman.2018.05.068},

issn = {0301-4797},

year  = {2018},

date = {2018-01-01},

journal = {Journal of Environmental Management},

volume = {222},

pages = {428 - 435},

abstract = {In this study, nuclear magnetic resonance (1H NMR) spectroscopic profiling was used to provide a more comprehensive view of microbial metabolites associated with poor reactor performance in a full-scale 4 MW mesophilic agricultural biogas plant under fully operational and also under inhibited conditions. Multivariate analyses were used to assess the significance of differences between reactors whereas artificial neural networks (ANN) were used to identify the key metabolites responsible for inhibition and their network of interaction. Based on the results of nm-MDS ordination the subsamples of each reactor were similar, but not identical, despite homogenization of the full-scale reactors before sampling. Hence, a certain extent of variability due to the size of the system under analysis was transferred into metabolome analysis. Multivariate analysis showed that fully active reactors were clustered separately from those containing inhibited reactor metabolites and were significantly different. Furthermore, the three distinct inhibited states were significantly different from each other. The inhibited metabolomes were enriched in acetate, caprylate, trimethylamine, thymine, pyruvate, alanine, xanthine and succinate. The differences in the metabolic fingerprint between inactive and fully active reactors observed in this study resembled closely the metabolites differentiating the (sub) acute rumen acidosis inflicted and healthy rumen metabolomes, creating thus favorable conditions for the growth and activity of pathogenic bacteria. The consistency of our data with those reported before for rumen ecosystems shows that 1H NMR based metabolomics is a reliable approach for the evaluation of metabolic events at full-scale biogas reactors.},

keywords = {1H NMR, Biogas plant, Chenomix, Metabolomics, Reactor inhibition},

pubstate = {published},

tppubtype = {article}

}