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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.
Murovec, Bostjan; Makuc, Damjan; Kolbl Repinc, Sabina; Prevorsek, Zala; Zavec, Domen; Sket, Robert; Pecnik, Klemen; Plavec, Janez; Stres, Blaz.
Afiliação
  • Murovec B; Laboratory for Artificial Sight and Automation, Faculty of Electrical Sciences, University of Ljubljana, Ljubljana, Slovenia.
  • Makuc D; Slovenian NMR Centre, National Institute of Chemistry, Hajdrihova 19, SI-1000, Ljubljana, Slovenia.
  • Kolbl Repinc S; Faculty of Civil and Geodetic Engineering, Hajdrihova 28, SI-1000, Ljubljana, Slovenia.
  • Prevorsek Z; Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
  • Zavec D; Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
  • Sket R; Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia.
  • Pecnik K; Slovenian NMR Centre, National Institute of Chemistry, Hajdrihova 19, SI-1000, Ljubljana, Slovenia.
  • Plavec J; Slovenian NMR Centre, National Institute of Chemistry, Hajdrihova 19, SI-1000, Ljubljana, Slovenia.
  • Stres B; Faculty of Civil and Geodetic Engineering, Hajdrihova 28, SI-1000, Ljubljana, Slovenia; Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia; Center for Clinical Neurophysiology, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia. Electronic
J Environ Manage ; 222: 428-435, 2018 Sep 15.
Article em En | MEDLINE | ID: mdl-29894946
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Metabolômica / Biocombustíveis / Espectroscopia de Prótons por Ressonância Magnética Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Metabolômica / Biocombustíveis / Espectroscopia de Prótons por Ressonância Magnética Idioma: En Ano de publicação: 2018 Tipo de documento: Article