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Acetobacter species play an import role during cocoa fermentation. However, Acetobacter ghanensis and Acetobacter senegalensis are outcompeted during fermentation of the cocoa pulp-bean mass, whereas Acetobacter pasteurianus prevails. In this paper, an in silico approach aimed at delivering some insights into the possible metabolic adaptations of A. ghanensis LMG 23848T and A. senegalensis 108B, two candidate starter culture strains for cocoa fermentation processes, by reconstructing genome-scale metabolic models (GEMs). Therefore, genome sequence data of a selection of strains of Acetobacter species were used to perform a comparative genomic analysis. Combining the predicted orthologous groups of protein-encoding genes from the Acetobacter genomes with gene-reaction rules of GEMs from two reference bacteria, namely a previously manually curated model of A. pasteurianus 386B (iAp386B454) and two manually curated models of Escherichia coli (EcoCyc and iJO1366), allowed to predict the set of reactions present in A. ghanensis LMG 23848T and A. senegalensis 108B. The predicted metabolic network was manually curated using genome re-annotation data, followed by the reconstruction of species-specific GEMs. This approach additionally revealed possible differences concerning the carbon core metabolism and redox metabolism among Acetobacter species, pointing to a hitherto unexplored metabolic diversity. More specifically, the presence or absence of reactions related to citrate catabolism and the glyoxylate cycle for assimilation of C2 compounds provided not only new insights into cocoa fermentation but also interesting guidelines for future research. In general, the A. ghanensis LMG 23848T and A. senegalensis 108B GEMs, reconstructed in a semi-automated way, provided a proof-of-concept toward accelerated formation of GEMs of candidate functional starter cultures for food fermentation processes.

Abstract Background Leptin-deficient ob/ob mice and leptin receptor-deficient db/db mice are commonly used mice models mimicking the conditions of obesity and type 2 diabetes development. However, although ob/ob and db/db mice are similarly gaining weight and developing massive obesity, db/db mice are more diabetic than ob/ob mice. It remains still unclear why targeting the same pathway—leptin signaling—leads to the development of two different phenotypes. Given that gut microbes dialogue with the host via different metabolites (e.g., short-chain fatty acids) but also contribute to the regulation of bile acids metabolism, we investigated whether inflammatory markers, bacterial components, bile acids, short-chain fatty acids, and gut microbes could contribute to explain the specific phenotype discriminating the onset of an obese and/or a diabetic state in ob/ob and db/db mice. Results Six-week-old ob/ob and db/db mice were followed for 7 weeks; they had comparable body weight, fat mass, and lean mass gain, confirming their severely obese status. However, as expected, the glucose metabolism and the glucose-induced insulin secretion were significantly different between ob/ob and db/db mice. Strikingly, the fat distribution was different, with db/db mice having more subcutaneous and ob/ob mice having more epididymal fat. In addition, liver steatosis was more pronounced in the ob/ob mice than in db/db mice. We also found very distinct inflammatory profiles between ob/ob and db/db mice, with a more pronounced inflammatory tone in the liver for ob/ob mice as compared to a higher inflammatory tone in the (subcutaneous) adipose tissue for db/db mice. When analyzing the gut microbiota composition, we found that the quantity of 19 microbial taxa was in some way affected by the genotype. Furthermore, we also show that serum LPS concentration, hepatic bile acid content, and cecal short-chain fatty acid profiles were differently affected by the two genotypes. Conclusion Taken together, our results elucidate potential mechanisms implicated in the development of an obese or a diabetic state in two genetic models characterized by an altered leptin signaling. We propose that these differences could be linked to specific inflammatory tones, serum LPS concentration, bile acid metabolism, short-chain fatty acid profile, and gut microbiota composition. Video abstract.

Acetobacter pasteurianus 386B is a candidate functional starter culture for the cocoa bean fermentation process. To allow in silico simulations of its related metabolism in response to different environmental conditions, a genome-scale metabolic model for A. pasteurianus 386B was reconstructed. This is the first genome-scale metabolic model reconstruction for a member of the genus Acetobacter. The metabolic network reconstruction process was based on extensive genome re-annotation and comparative genomics analyses. The information content related to the functional annotation of metabolic enzymes and transporters was placed in a metabolic context by exploring and curating a Pathway/Genome Database of A. pasteurianus 386B using the Pathway Tools software. Metabolic reactions and curated gene-protein-reaction associations were bundled into a genome-scale metabolic model of A. pasteurianus 386B, named iAp386B454, containing 454 genes, 322 reactions, and 296 metabolites embedded in two cellular compartments. The reconstructed model was validated by performing growth experiments in a defined medium, which revealed that lactic acid as the sole carbon source could sustain growth of this strain. Further, the reconstruction of the A. pasteurianus 386B genome-scale metabolic model revealed knowledge gaps concerning the metabolism of this strain, especially related to the biosynthesis of its cell envelope and the presence or absence of metabolite transporters.

The global obesity epidemic continues to rise worldwide. In this context, unraveling new interconnections between biological systems involved in obesity etiology is highly relevant. Dysregulation of the endocannabinoidome (eCBome) is associated with metabolic complications in obesity. This study aims at deciphering new associations between circulating endogenous bioactive lipids belonging to the eCBome and metabolic parameters in a population of overweight or obese individuals with metabolic syndrome. To this aim, we combined different multivariate exploratory analysis methods: canonical correlation analysis and principal component analysis, revealed associations between eCBome subsets, and metabolic parameters such as leptin, lipopolysaccharide-binding protein, and non-esterified fatty acids (NEFA). Subsequent construction of predictive regression models according to the linear combination of selected endocannabinoids demonstrates good prediction performance for NEFA. Descriptive approaches reveal the importance of specific circulating endocannabinoids and key related congeners to explain variance in the metabolic parameters in our cohort. Analysis of quartiles confirmed that these bioactive lipids were significantly higher in individuals characterized by important levels for aforementioned metabolic variables. In conclusion, by proposing a methodology for the exploration of large-scale data, our study offers additional evidence of the existence of an interplay between eCBome related-entities and metabolic parameters known to be altered in obesity.

Akkermansia muciniphila is considered as one of the next-generation beneficial bacteria in the context of obesity and associated metabolic disorders. Although a first proof-of-concept of its beneficial effects has been established in the context of metabolic syndrome in humans, mechanisms are not yet fully understood. This study aimed at deciphering whether the bacterium exerts its beneficial properties through the modulation of the endocannabinoidome (eCBome). Circulating levels of 25 endogenous endocannabinoid-related lipids were quantified by liquid chromatography with tandem mass spectrometry (LC-MS/MS) in the plasma of overweight or obese individuals before and after a 3 months intervention consisting of the daily ingestion of either alive or pasteurized A. muciniphila. Results from multivariate analyses suggested that the beneficial effects of A. muciniphila were not linked to an overall modification of the eCBome. However, subsequent univariate analysis showed that the decrease in 1-Palmitoyl-glycerol (1-PG) and 2-Palmitoyl-glycerol (2-PG), two eCBome lipids, observed in the placebo group was significantly counteracted by the alive bacterium, and to a lower extent by the pasteurized form. We also discovered that 1- and 2-PG are endogenous activators of peroxisome proliferator-activated receptor alpha (PPARα). We hypothesize that PPARα activation by mono-palmitoyl-glycerols may underlie part of the beneficial metabolic effects induced by A. muciniphila in human metabolic syndrome.