Perturbation of the gut microbiome by Prevotella spp. enhances host susceptibility to mucosal inflammation.

Diverse microbial signatures within the intestinal microbiota have been associated with intestinal and systemic inflammatory diseases, but whether these candidate microbes actively modulate host phenotypes or passively expand within the altered microbial ecosystem is frequently not known. Here we demonstrate that colonization of mice with a member of the genus Prevotella, which has been previously associated to colitis in mice, exacerbates intestinal inflammation. Our analysis revealed that Prevotella intestinalis alters composition and function of the ecosystem resulting in a reduction of short-chain fatty acids, specifically acetate, and consequently a decrease in intestinal IL-18 levels during steady state. Supplementation of IL-18 to Prevotella-colonized mice was sufficient to reduce intestinal inflammation. Hence, we conclude that intestinal Prevotella colonization results in metabolic changes in the microbiota, which reduce IL-18 production and consequently exacerbate intestinal inflammation, and potential systemic autoimmunity.

Synergistic biodegradation of aromatic-aliphatic copolyester plastic by a marine microbial consortium.

The degradation of synthetic polymers by marine microorganisms is not as well understood as the degradation of plastics in soil and compost. Here, we use metagenomics, metatranscriptomics and metaproteomics to study the biodegradation of an aromatic-aliphatic copolyester blend by a marine microbial enrichment culture. The culture can use the plastic film as the sole carbon source, reaching maximum conversion to CO2 and biomass in around 15 days. The consortium degrades the polymer synergistically, with different degradation steps being performed by different community members. We identify six putative PETase-like enzymes and four putative MHETase-like enzymes, with the potential to degrade aliphatic-aromatic polymers and their degradation products, respectively. Our results show that, although there are multiple genes and organisms with the potential to perform each degradation step, only a few are active during biodegradation.

The fate of lysine: Non-targeted stable isotope analysis reveals parallel ways for lysine catabolization in Phaeobacter inhibens.

For a detailed investigation of the degradation of lysine in Phaeobacter inhibens DSM 17395, stable isotope experiments with uniformly 13C labeled L-lysine were carried out with lysine adapted cells and the metabolites were analyzed using GC/MS and HPLC/MS. A non-targeted stable isotope analysis was used which compares labeled and not labeled samples to determine the Mass Isotopomer Distribution not only for known metabolites but for all labeled compounds in our GC/MS analysis. We show that P. inhibens uses at least two parallel pathways for the first degradation steps of lysine. Further investigations identified L-pipecolate as an L-lysine degradation intermediate in P. inhibens. The analysis of HPLC/MS data as well as the labeling data of tricarboxylic acid (TCA) cycle intermediates show that L-lysine is not only catabolized directly to acetyl-CoA but also via the ethylmalonyl-CoA-pathway, leading to entry points into the TCA cycle via acetyl-CoA, succinyl-CoA, and malate. Altogether the presented data give a detailed insight into the catabolization of L-lysine following the fate of 13C labeled carbon via several ways into the TCA cycle.

Clostridioides difficile 630Δerm in silico and in vivo - quantitative growth and extensive polysaccharide secretion.

Antibiotic-associated infections with Clostridioides difficile are a severe and often lethal risk for hospitalized patients, and can also affect populations without these classical risk factors. For a rational design of therapeutical concepts, a better knowledge of the metabolism of the pathogen is crucial. Metabolic modeling can provide a simulation of quantitative growth and usage of metabolic pathways, leading to a deeper understanding of the organism. Here, we present an elaborate genome-scale metabolic model of C. difficile 630Δerm. The model iHD992 includes experimentally determined product and substrate uptake rates and is able to simulate the energy metabolism and quantitative growth of C. difficile. Dynamic flux balance analysis was used for time-resolved simulations of the quantitative growth in two different media. The model predicts oxidative Stickland reactions and glucose degradation as main sources of energy, while the resulting reduction potential is mostly used for acetogenesis via the Wood-Ljungdahl pathway. Initial modeling experiments did not reproduce the observed growth behavior before the production of large quantities of a previously unknown polysaccharide was detected. Combined genome analysis and laboratory experiments indicated that the polysaccharide is an acetylated glucose polymer. Time-resolved simulations showed that polysaccharide secretion was coupled to growth even during unstable glucose uptake in minimal medium. This is accomplished by metabolic shifts between active glycolysis and gluconeogenesis which were also observed in laboratory experiments.