Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Proteomic analysis of nitrate-dependent acetone degradation by Alicycliphilus denitrificans strain BC

Alicycliphilus denitrificans strain BC grows anaerobically on acetone with nitrate as electron acceptor. Comparative proteomics of cultures of A. denitrificans strain BC grown on either acetone or acetate with nitrate was performed to study the enzymes involved in the acetone degradation pathway. In the proposed acetone degradation pathway, an acetone carboxylase converts acetone to acetoacetate, an AMP-dependent synthetase/ligase converts acetoacetate to acetoacetyl-CoA, and an acetyl-CoA acetyltransferase cleaves acetoacetyl-CoA to two acetyl-CoA. We also found a putative aldehyde dehydrogenase associated with acetone degradation. This enzyme functioned as a -hydroxybutyrate dehydrogenase catalyzing the conversion of surplus acetoacetate to -hydroxybutyrate that may be converted to the energy and carbon storage compound, poly--hydroxybutyrate. Accordingly, we confirmed the formation of poly-?-hydroxybutyrate in acetone-grown cells of strain BC. Our findings provide insight in nitrate-dependent acetone degradation that is activated by carboxylation of acetone. This will aid studies of similar pathways found in other microorganisms degrading acetone with nitrate or sulfate as electron acceptor.