Lactococcus lactis subsp. cremoris MG1363 is a paradigm strain for lactococci used in industrial dairy fermentations. However, despite of its importance for process development, no genome-scale metabolic model has been reported thus far. Moreover, current models for other lactococci only focus on growth and sugar degradation. A metabolic model that includes nitrogen metabolism and flavor-forming pathways is instrumental for the understanding and designing new industrial applications of these lactic acid bacteria. A genome-scale, constraint-based model of the metabolism and transport in L. lactis MG1363, accounting for 518 genes, 754 reactions, and 650 metabolites, was developed and experimentally validated. Fifty-nine reactions are directly or indirectly involved in flavor formation. Flux Balance Analysis and Flux Variability Analysis were used to investigate flux distributions within the whole metabolic network. Anaerobic carbon-limited continuous cultures were used for estimating the energetic parameters. A thorough model-driven analysis showing a highly flexible nitrogen metabolism, e.g., branched-chain amino acid catabolism which coupled with the redox balance, is pivotal for the prediction of the formation of different flavor compounds. Furthermore, the model predicted the formation of volatile sulfur compounds as a result of the fermentation. These products were subsequently identified in the experimental fermentations carried out. Thus, the genome-scale metabolic model couples the carbon and nitrogen metabolism in L. lactis MG1363 with complete known catabolic pathways leading to flavor formation. The model provided valuable insights into the metabolic networks underlying flavor formation and has the potential to contribute to new developments in dairy industries and cheese-flavor research.

It is known that the gastrointestinal tract (GIT) microbiota responds to different antibiotics in different ways and that while some antibiotics do not induce disturbances of the community, others drastically influence the richness, diversity, and prevalence of bacterial taxa. However, the metabolic consequences thereof, independent of the degree of the community shifts, are not clearly understood. In a recent article, we used an integrative OMICS approach to provide new insights into the metabolic shifts caused by antibiotic disturbance. The study presented here further suggests that specific bacterial lineage blooms occurring at defined stages of antibiotic intervention are mostly associated with organisms that possess improved survival and colonization mechanisms, such as those of the Enterococcus, Blautia, Faecalibacterium, and Akkermansia genera. The study also provides an overview of the most variable metabolic functions affected as a consequence of a β-lactam antibiotic intervention. Thus, we observed that anabolic sugar metabolism, the production of acetyl donors and the synthesis and degradation of intestinal/colonic epithelium components were among the most variable functions during the intervention. We are aware that these results have been established with a single patient and will require further confirmation with a larger group of individuals and with other antibiotics. Future directions for exploration of the effects of antibiotic interventions are discussed.

Clostridium difficile infections are an emerging health problem in the modern hospital environment. Severe alterations of the gut microbiome with loss of resistance to colonization against C. difficile are thought to be the major trigger, but there is no clear concept of how C. difficile infection evolves and which microbiological factors are involved. We sequenced 16S rRNA amplicons generated from DNA and RNA/cDNA of fecal samples from three groups of individuals by FLX technology: (i) healthy controls (no antibiotic therapy); (ii) individuals receiving antibiotic therapy (Ampicillin/Sulbactam, cephalosporins, and fluoroquinolones with subsequent development of C. difficile infection or (iii) individuals receiving antibiotic therapy without C. difficile infection. We compared the effects of the three different antibiotic classes on the intestinal microbiome and the effects of alterations of the gut microbiome on C. difficile infection at the DNA (total microbiota) and rRNA (potentially active) levels. A comparison of antibiotic classes showed significant differences at DNA level, but not at RNA level. Among individuals that developed or did not develop a C. difficile infection under antibiotics we found no significant differences. We identified single species that were up- or down regulated in individuals receiving antibiotics who developed the infection compared to non-infected individuals. We found no significant differences in the global composition of the transcriptionally active gut microbiome associated with C. difficile infections. We suggest that up- and down regulation of specific bacterial species may be involved in colonization resistance against C. difficile providing a potential therapeutic approach through specific manipulation of the intestinal microbiome.